support ltx-2 training

diffsynth/configs/model_configs.py

@@ -607,6 +607,12 @@ ltx2_series = [
         "model_class": "diffsynth.models.ltx2_dit.LTXModel",
         "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_dit.LTXModelStateDictConverter",
     },
+    {
+        "model_hash": "c567aaa37d5ed7454c73aa6024458661",
+        "model_name": "ltx2_dit",
+        "model_class": "diffsynth.models.ltx2_dit.LTXModel",
+        "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_dit.LTXModelStateDictConverter",
+    },
     {
         # Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
         "model_hash": "aca7b0bbf8415e9c98360750268915fc",
@@ -614,6 +620,12 @@ ltx2_series = [
         "model_class": "diffsynth.models.ltx2_video_vae.LTX2VideoEncoder",
         "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_video_vae.LTX2VideoEncoderStateDictConverter",
     },
+    {
+        "model_hash": "7f7e904a53260ec0351b05f32153754b",
+        "model_name": "ltx2_video_vae_encoder",
+        "model_class": "diffsynth.models.ltx2_video_vae.LTX2VideoEncoder",
+        "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_video_vae.LTX2VideoEncoderStateDictConverter",
+    },
     {
         # Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
         "model_hash": "aca7b0bbf8415e9c98360750268915fc",
@@ -621,6 +633,12 @@ ltx2_series = [
         "model_class": "diffsynth.models.ltx2_video_vae.LTX2VideoDecoder",
         "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_video_vae.LTX2VideoDecoderStateDictConverter",
     },
+    {
+        "model_hash": "dc6029ca2825147872b45e35a2dc3a97",
+        "model_name": "ltx2_video_vae_decoder",
+        "model_class": "diffsynth.models.ltx2_video_vae.LTX2VideoDecoder",
+        "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_video_vae.LTX2VideoDecoderStateDictConverter",
+    },
     {
         # Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
         "model_hash": "aca7b0bbf8415e9c98360750268915fc",
@@ -628,6 +646,12 @@ ltx2_series = [
         "model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioDecoder",
         "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioDecoderStateDictConverter",
     },
+    {
+        "model_hash": "7d7823dde8f1ea0b50fb07ac329dd4cb",
+        "model_name": "ltx2_audio_vae_decoder",
+        "model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioDecoder",
+        "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioDecoderStateDictConverter",
+    },
     {
         # Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
         "model_hash": "aca7b0bbf8415e9c98360750268915fc",
@@ -635,16 +659,34 @@ ltx2_series = [
         "model_class": "diffsynth.models.ltx2_audio_vae.LTX2Vocoder",
         "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2VocoderStateDictConverter",
     },
-    # { # not used currently
+    {
-    #     # Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
+        "model_hash": "f471360f6b24bef702ab73133d9f8bb9",
-    #     "model_hash": "aca7b0bbf8415e9c98360750268915fc",
+        "model_name": "ltx2_audio_vocoder",
-    #     "model_name": "ltx2_audio_vae_encoder",
+        "model_class": "diffsynth.models.ltx2_audio_vae.LTX2Vocoder",
-    #     "model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioEncoder",
+        "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2VocoderStateDictConverter",
-    #     "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioEncoderStateDictConverter",
+    },
-    # },
     {
         # Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
         "model_hash": "aca7b0bbf8415e9c98360750268915fc",
+        "model_name": "ltx2_audio_vae_encoder",
+        "model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioEncoder",
+        "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioEncoderStateDictConverter",
+    },
+    {
+        "model_hash": "29338f3b95e7e312a3460a482e4f4554",
+        "model_name": "ltx2_audio_vae_encoder",
+        "model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioEncoder",
+        "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioEncoderStateDictConverter",
+    },
+    {
+        # Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
+        "model_hash": "aca7b0bbf8415e9c98360750268915fc",
+        "model_name": "ltx2_text_encoder_post_modules",
+        "model_class": "diffsynth.models.ltx2_text_encoder.LTX2TextEncoderPostModules",
+        "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_text_encoder.LTX2TextEncoderPostModulesStateDictConverter",
+    },
+    {
+        "model_hash": "981629689c8be92a712ab3c5eb4fc3f6",
         "model_name": "ltx2_text_encoder_post_modules",
         "model_class": "diffsynth.models.ltx2_text_encoder.LTX2TextEncoderPostModules",
         "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_text_encoder.LTX2TextEncoderPostModulesStateDictConverter",

diffsynth/diffusion/loss.py

@@ -28,6 +28,36 @@ def FlowMatchSFTLoss(pipe: BasePipeline, **inputs):
     return loss
 
 
+def FlowMatchSFTAudioVideoLoss(pipe: BasePipeline, **inputs):
+    max_timestep_boundary = int(inputs.get("max_timestep_boundary", 1) * len(pipe.scheduler.timesteps))
+    min_timestep_boundary = int(inputs.get("min_timestep_boundary", 0) * len(pipe.scheduler.timesteps))
+
+    timestep_id = torch.randint(min_timestep_boundary, max_timestep_boundary, (1,))
+    timestep = pipe.scheduler.timesteps[timestep_id].to(dtype=pipe.torch_dtype, device=pipe.device)
+    
+    # video
+    noise = torch.randn_like(inputs["input_latents"])
+    inputs["video_latents"] = pipe.scheduler.add_noise(inputs["input_latents"], noise, timestep)
+    training_target = pipe.scheduler.training_target(inputs["input_latents"], noise, timestep)
+    
+    # audio
+    if inputs.get("audio_input_latents") is not None:
+        audio_noise = torch.randn_like(inputs["audio_input_latents"])
+        inputs["audio_latents"] = pipe.scheduler.add_noise(inputs["audio_input_latents"], audio_noise, timestep)
+        training_target_audio = pipe.scheduler.training_target(inputs["audio_input_latents"], audio_noise, timestep)
+
+    models = {name: getattr(pipe, name) for name in pipe.in_iteration_models}
+    noise_pred, noise_pred_audio = pipe.model_fn(**models, **inputs, timestep=timestep)
+
+    loss = torch.nn.functional.mse_loss(noise_pred.float(), training_target.float())
+    loss = loss * pipe.scheduler.training_weight(timestep)
+    if inputs.get("audio_input_latents") is not None:
+        loss_audio = torch.nn.functional.mse_loss(noise_pred_audio.float(), training_target_audio.float())
+        loss_audio = loss_audio * pipe.scheduler.training_weight(timestep)
+        loss = loss + loss_audio
+    return loss
+
+
 def DirectDistillLoss(pipe: BasePipeline, **inputs):
     pipe.scheduler.set_timesteps(inputs["num_inference_steps"])
     pipe.scheduler.training = True

diffsynth/models/ltx2_audio_vae.py

@@ -5,8 +5,65 @@ import einops
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
+import torchaudio
 from .ltx2_common import VideoLatentShape, AudioLatentShape, Patchifier, NormType, build_normalization_layer
 
+
+class AudioProcessor(nn.Module):
+    """Converts audio waveforms to log-mel spectrograms with optional resampling."""
+
+    def __init__(
+        self,
+        sample_rate: int = 16000,
+        mel_bins: int = 64,
+        mel_hop_length: int = 160,
+        n_fft: int = 1024,
+    ) -> None:
+        super().__init__()
+        self.sample_rate = sample_rate
+        self.mel_transform = torchaudio.transforms.MelSpectrogram(
+            sample_rate=sample_rate,
+            n_fft=n_fft,
+            win_length=n_fft,
+            hop_length=mel_hop_length,
+            f_min=0.0,
+            f_max=sample_rate / 2.0,
+            n_mels=mel_bins,
+            window_fn=torch.hann_window,
+            center=True,
+            pad_mode="reflect",
+            power=1.0,
+            mel_scale="slaney",
+            norm="slaney",
+        )
+
+    def resample_waveform(
+        self,
+        waveform: torch.Tensor,
+        source_rate: int,
+        target_rate: int,
+    ) -> torch.Tensor:
+        """Resample waveform to target sample rate if needed."""
+        if source_rate == target_rate:
+            return waveform
+        resampled = torchaudio.functional.resample(waveform, source_rate, target_rate)
+        return resampled.to(device=waveform.device, dtype=waveform.dtype)
+
+    def waveform_to_mel(
+        self,
+        waveform: torch.Tensor,
+        waveform_sample_rate: int,
+    ) -> torch.Tensor:
+        """Convert waveform to log-mel spectrogram [batch, channels, time, n_mels]."""
+        waveform = self.resample_waveform(waveform, waveform_sample_rate, self.sample_rate)
+
+        mel = self.mel_transform(waveform)
+        mel = torch.log(torch.clamp(mel, min=1e-5))
+
+        mel = mel.to(device=waveform.device, dtype=waveform.dtype)
+        return mel.permute(0, 1, 3, 2).contiguous()
+
+
 class AudioPatchifier(Patchifier):
     def __init__(
         self,

diffsynth/models/ltx2_dit.py

@@ -1446,6 +1446,6 @@ class LTXModel(torch.nn.Module):
             cross_pe_max_pos = max(self.positional_embedding_max_pos[0], self.audio_positional_embedding_max_pos[0])
         self._init_preprocessors(cross_pe_max_pos)
         video = Modality(video_latents, video_timesteps, video_positions, video_context)
-        audio = Modality(audio_latents, audio_timesteps, audio_positions, audio_context)
+        audio = Modality(audio_latents, audio_timesteps, audio_positions, audio_context) if audio_latents is not None else None
         vx, ax = self._forward(video=video, audio=audio, perturbations=None)
         return vx, ax

diffsynth/pipelines/ltx2_audio_video.py

@@ -18,7 +18,7 @@ from ..diffusion.base_pipeline import BasePipeline, PipelineUnit
 from ..models.ltx2_text_encoder import LTX2TextEncoder, LTX2TextEncoderPostModules, LTXVGemmaTokenizer
 from ..models.ltx2_dit import LTXModel
 from ..models.ltx2_video_vae import LTX2VideoEncoder, LTX2VideoDecoder, VideoLatentPatchifier
-from ..models.ltx2_audio_vae import LTX2AudioEncoder, LTX2AudioDecoder, LTX2Vocoder, AudioPatchifier
+from ..models.ltx2_audio_vae import LTX2AudioEncoder, LTX2AudioDecoder, LTX2Vocoder, AudioPatchifier, AudioProcessor
 from ..models.ltx2_upsampler import LTX2LatentUpsampler
 from ..models.ltx2_common import VideoLatentShape, AudioLatentShape, VideoPixelShape, get_pixel_coords, VIDEO_SCALE_FACTORS
 from ..utils.data.media_io_ltx2 import ltx2_preprocess
@@ -50,6 +50,7 @@ class LTX2AudioVideoPipeline(BasePipeline):
 
         self.video_patchifier: VideoLatentPatchifier = VideoLatentPatchifier(patch_size=1)
         self.audio_patchifier: AudioPatchifier = AudioPatchifier(patch_size=1)
+        self.audio_processor: AudioProcessor = AudioProcessor()
 
         self.in_iteration_models = ("dit",)
         self.units = [
@@ -57,6 +58,7 @@ class LTX2AudioVideoPipeline(BasePipeline):
             LTX2AudioVideoUnit_ShapeChecker(),
             LTX2AudioVideoUnit_PromptEmbedder(),
             LTX2AudioVideoUnit_NoiseInitializer(),
+            LTX2AudioVideoUnit_InputAudioEmbedder(),
             LTX2AudioVideoUnit_InputVideoEmbedder(),
             LTX2AudioVideoUnit_InputImagesEmbedder(),
         ]
@@ -95,7 +97,7 @@ class LTX2AudioVideoPipeline(BasePipeline):
             stage2_lora_config.download_if_necessary()
             pipe.stage2_lora_path = stage2_lora_config.path
         # Optional, currently not used
-        # pipe.audio_vae_encoder = model_pool.fetch_model("ltx2_audio_vae_encoder")
+        pipe.audio_vae_encoder = model_pool.fetch_model("ltx2_audio_vae_encoder")
 
         # VRAM Management
         pipe.vram_management_enabled = pipe.check_vram_management_state()
@@ -157,7 +159,6 @@ class LTX2AudioVideoPipeline(BasePipeline):
         num_frames=121,
         # Classifier-free guidance
         cfg_scale: Optional[float] = 3.0,
-        cfg_merge: Optional[bool] = False,
         # Scheduler
         num_inference_steps: Optional[int] = 40,
         # VAE tiling
@@ -186,7 +187,7 @@ class LTX2AudioVideoPipeline(BasePipeline):
             "input_images": input_images, "input_images_indexes": input_images_indexes, "input_images_strength": input_images_strength,
             "seed": seed, "rand_device": rand_device,
             "height": height, "width": width, "num_frames": num_frames,
-            "cfg_scale": cfg_scale, "cfg_merge": cfg_merge,
+            "cfg_scale": cfg_scale,
             "tiled": tiled, "tile_size_in_pixels": tile_size_in_pixels, "tile_overlap_in_pixels": tile_overlap_in_pixels,
             "tile_size_in_frames": tile_size_in_frames, "tile_overlap_in_frames": tile_overlap_in_frames,
             "use_two_stage_pipeline": use_two_stage_pipeline, "use_distilled_pipeline": use_distilled_pipeline,
@@ -422,7 +423,7 @@ class LTX2AudioVideoUnit_NoiseInitializer(PipelineUnit):
 
     def process_stage(self, pipe: LTX2AudioVideoPipeline, height, width, num_frames, seed, rand_device, frame_rate=24.0):
         video_pixel_shape = VideoPixelShape(batch=1, frames=num_frames, width=width, height=height, fps=frame_rate)
-        video_latent_shape = VideoLatentShape.from_pixel_shape(shape=video_pixel_shape, latent_channels=pipe.video_vae_encoder.latent_channels)
+        video_latent_shape = VideoLatentShape.from_pixel_shape(shape=video_pixel_shape, latent_channels=128)
         video_noise = pipe.generate_noise(video_latent_shape.to_torch_shape(), seed=seed, rand_device=rand_device)
 
         latent_coords = pipe.video_patchifier.get_patch_grid_bounds(output_shape=video_latent_shape, device=pipe.device)
@@ -455,17 +456,48 @@ class LTX2AudioVideoUnit_NoiseInitializer(PipelineUnit):
 class LTX2AudioVideoUnit_InputVideoEmbedder(PipelineUnit):
     def __init__(self):
         super().__init__(
-            input_params=("input_video", "video_noise", "audio_noise", "tiled", "tile_size", "tile_stride"),
+            input_params=("input_video", "video_noise", "tiled", "tile_size_in_pixels", "tile_overlap_in_pixels"),
-            output_params=("video_latents", "audio_latents"),
+            output_params=("video_latents", "input_latents"),
             onload_model_names=("video_vae_encoder")
         )
 
-    def process(self, pipe: LTX2AudioVideoPipeline, input_video, video_noise, audio_noise, tiled, tile_size, tile_stride):
+    def process(self, pipe: LTX2AudioVideoPipeline, input_video, video_noise, tiled, tile_size_in_pixels, tile_overlap_in_pixels):
         if input_video is None:
-            return {"video_latents": video_noise, "audio_latents": audio_noise}
+            return {"video_latents": video_noise}
         else:
-            # TODO: implement video-to-video
+            pipe.load_models_to_device(self.onload_model_names)
-            raise NotImplementedError("Video-to-video not implemented yet.")
+            input_video = pipe.preprocess_video(input_video)
+            input_latents = pipe.video_vae_encoder.encode(input_video, tiled, tile_size_in_pixels, tile_overlap_in_pixels).to(dtype=pipe.torch_dtype, device=pipe.device)
+            if pipe.scheduler.training:
+                return {"video_latents": input_latents, "input_latents": input_latents}
+            else:
+                # TODO: implement video-to-video
+                raise NotImplementedError("Video-to-video not implemented yet.")
+
+class LTX2AudioVideoUnit_InputAudioEmbedder(PipelineUnit):
+    def __init__(self):
+        super().__init__(
+            input_params=("input_audio", "audio_noise"),
+            output_params=("audio_latents", "audio_input_latents", "audio_positions", "audio_latent_shape"),
+            onload_model_names=("audio_vae_encoder",)
+        )
+
+    def process(self, pipe: LTX2AudioVideoPipeline, input_audio, audio_noise):
+        if input_audio is None:
+            return {"audio_latents": audio_noise}
+        else:
+            input_audio, sample_rate = input_audio
+            pipe.load_models_to_device(self.onload_model_names)
+            input_audio = pipe.audio_processor.waveform_to_mel(input_audio.unsqueeze(0), waveform_sample_rate=sample_rate).to(dtype=pipe.torch_dtype)
+            audio_input_latents = pipe.audio_vae_encoder(input_audio)
+            audio_noise = torch.randn_like(audio_input_latents)
+            audio_latent_shape = AudioLatentShape.from_torch_shape(audio_input_latents.shape)
+            audio_positions = pipe.audio_patchifier.get_patch_grid_bounds(audio_latent_shape, device=pipe.device)
+            if pipe.scheduler.training:
+                return {"audio_latents": audio_input_latents, "audio_input_latents": audio_input_latents, "audio_positions": audio_positions, "audio_latent_shape": audio_latent_shape}
+            else:
+                # TODO: implement video-to-video
+                raise NotImplementedError("Video-to-video not implemented yet.")
 
 class LTX2AudioVideoUnit_InputImagesEmbedder(PipelineUnit):
     def __init__(self):
@@ -530,9 +562,12 @@ def model_fn_ltx2(
     video_timesteps = timestep.repeat(1, video_latents.shape[1], 1)
     if denoise_mask_video is not None:
         video_timesteps = video_patchifier.patchify(denoise_mask_video) * video_timesteps
-    _, c_a, _, mel_bins  = audio_latents.shape
+    if audio_latents is not None:
-    audio_latents = audio_patchifier.patchify(audio_latents)
+        _, c_a, _, mel_bins  = audio_latents.shape
-    audio_timesteps = timestep.repeat(1, audio_latents.shape[1], 1)
+        audio_latents = audio_patchifier.patchify(audio_latents)
+        audio_timesteps = timestep.repeat(1, audio_latents.shape[1], 1)
+    else:
+        audio_timesteps = None
     #TODO: support gradient checkpointing in training
     vx, ax = dit(
         video_latents=video_latents,
@@ -546,5 +581,5 @@ def model_fn_ltx2(
     )
     # unpatchify
     vx = video_patchifier.unpatchify_video(vx, f, h, w)
-    ax = audio_patchifier.unpatchify_audio(ax, c_a, mel_bins)
+    ax = audio_patchifier.unpatchify_audio(ax, c_a, mel_bins) if ax is not None else None
     return vx, ax

examples/ltx2/model_inference/LTX-2-I2AV-DistilledPipeline.py

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer_distilled.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-I2AV-OneStage.py

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
 )

examples/ltx2/model_inference/LTX-2-I2AV-TwoStage.py

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Dolly-In.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Dolly-Left.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Dolly-Out.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Dolly-Right.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Jib-Down.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Jib-Up.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Static.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-DistilledPipeline.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer_distilled.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference/LTX-2-T2AV-OneStage.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
 )
@@ -40,3 +44,12 @@ write_video_audio_ltx2(
     fps=24,
     audio_sample_rate=24000,
 )
+
+
+        # ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        # ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        # ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
+        # ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        # ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        # ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_encoder.safetensors", **vram_config),
+        # ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),

examples/ltx2/model_inference/LTX-2-T2AV-TwoStage.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-I2AV-DistilledPipeline.py

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer_distilled.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-I2AV-OneStage.py

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
     vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,

examples/ltx2/model_inference_low_vram/LTX-2-I2AV-TwoStage.py

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Dolly-In.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Dolly-Left.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Dolly-Out.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Dolly-Right.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Jib-Down.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Jib-Up.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Static.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-DistilledPipeline.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer_distilled.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-OneStage.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
     vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,

examples/ltx2/model_inference_low_vram/LTX-2-T2AV-TwoStage.py

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
     device="cuda",
     model_configs=[
         ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
-        ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
         ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
     ],
     tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

examples/ltx2/model_training/full/LTX-2-T2AV-splited.sh

@@ -0,0 +1,35 @@
+# Splited Training
+accelerate launch examples/ltx2/model_training/train.py \
+  --dataset_base_path data/example_video_dataset/ltx2 \
+  --dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
+  --data_file_keys "video,input_audio" \
+  --extra_inputs "input_audio" \
+  --height 512 \
+  --width 768 \
+  --num_frames 49 \
+  --dataset_repeat 1 \
+  --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
+  --learning_rate 1e-4 \
+  --num_epochs 5 \
+  --remove_prefix_in_ckpt "pipe.dit." \
+  --output_path "./models/train/LTX2-T2AV-full-splited-cache" \
+  --trainable_models "dit" \
+  --use_gradient_checkpointing \
+  --task "sft:data_process"
+
+accelerate launch examples/ltx2/model_training/train.py \
+  --dataset_base_path ./models/train/LTX2-T2AV-full-splited-cache \
+  --data_file_keys "video,input_audio" \
+  --extra_inputs "input_audio" \
+  --height 512 \
+  --width 768 \
+  --num_frames 49 \
+  --dataset_repeat 100 \
+  --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
+  --learning_rate 1e-4 \
+  --num_epochs 5 \
+  --remove_prefix_in_ckpt "pipe.dit." \
+  --output_path "./models/train/LTX2-T2AV-full" \
+  --trainable_models "dit" \
+  --use_gradient_checkpointing \
+  --task "sft:train"

examples/ltx2/model_training/lora/LTX-2-T2AV-noaudio.sh

@@ -0,0 +1,56 @@
+# single stage training
+# accelerate launch examples/ltx2/model_training/train.py \
+#   --dataset_base_path data/example_video_dataset/ltx2 \
+#   --dataset_metadata_path data/example_video_dataset/ltx2_t2v.csv \
+#   --height 256 \
+#   --width 384 \
+#   --num_frames 25\
+#   --dataset_repeat 100 \
+#   --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors,DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
+#   --learning_rate 1e-4 \
+#   --num_epochs 5 \
+#   --remove_prefix_in_ckpt "pipe.dit." \
+#   --output_path "./models/train/LTX2-T2AV-noaudio_lora" \
+#   --lora_base_model "dit" \
+#   --lora_target_modules "to_k,to_q,to_v,to_out.0" \
+#   --lora_rank 32 \
+#   --use_gradient_checkpointing \
+#   --find_unused_parameters
+
+
+# Splited Training
+accelerate launch examples/ltx2/model_training/train.py \
+  --dataset_base_path data/example_video_dataset/ltx2 \
+  --dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
+  --height 256 \
+  --width 384 \
+  --num_frames 49\
+  --dataset_repeat 1 \
+  --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
+  --learning_rate 1e-4 \
+  --num_epochs 5 \
+  --remove_prefix_in_ckpt "pipe.dit." \
+  --output_path "./models/train/LTX2-T2AV-noaudio_lora-splited-cache" \
+  --lora_base_model "dit" \
+  --lora_target_modules "to_k,to_q,to_v,to_out.0" \
+  --lora_rank 32 \
+  --use_gradient_checkpointing \
+  --task "sft:data_process"
+
+
+accelerate launch examples/ltx2/model_training/train.py \
+  --dataset_base_path ./models/train/LTX2-T2AV-noaudio_lora-splited-cache \
+  --height 256 \
+  --width 384 \
+  --num_frames 49\
+  --dataset_repeat 100 \
+  --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
+  --learning_rate 1e-4 \
+  --num_epochs 5 \
+  --remove_prefix_in_ckpt "pipe.dit." \
+  --output_path "./models/train/LTX2-T2AV-noaudio_lora" \
+  --lora_base_model "dit" \
+  --lora_target_modules "to_k,to_q,to_v,to_out.0" \
+  --lora_rank 32 \
+  --use_gradient_checkpointing \
+  --task "sft:train"

examples/ltx2/model_training/lora/LTX-2-T2AV-splited.sh

@@ -0,0 +1,40 @@
+# Splited Training
+accelerate launch examples/ltx2/model_training/train.py \
+  --dataset_base_path data/example_video_dataset/ltx2 \
+  --dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
+  --data_file_keys "video,input_audio" \
+  --extra_inputs "input_audio" \
+  --height 512 \
+  --width 768 \
+  --num_frames 49 \
+  --dataset_repeat 1 \
+  --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
+  --learning_rate 1e-4 \
+  --num_epochs 5 \
+  --remove_prefix_in_ckpt "pipe.dit." \
+  --output_path "./models/train/LTX2-T2AV_lora-splited-cache" \
+  --lora_base_model "dit" \
+  --lora_target_modules "to_k,to_q,to_v,to_out.0" \
+  --lora_rank 32 \
+  --use_gradient_checkpointing \
+  --task "sft:data_process"
+
+
+accelerate launch examples/ltx2/model_training/train.py \
+  --dataset_base_path ./models/train/LTX2-T2AV_lora-splited-cache \
+  --data_file_keys "video,input_audio" \
+  --extra_inputs "input_audio" \
+  --height 512 \
+  --width 768 \
+  --num_frames 49 \
+  --dataset_repeat 100 \
+  --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
+  --learning_rate 1e-4 \
+  --num_epochs 5 \
+  --remove_prefix_in_ckpt "pipe.dit." \
+  --output_path "./models/train/LTX2-T2AV_lora" \
+  --lora_base_model "dit" \
+  --lora_target_modules "to_k,to_q,to_v,to_out.0" \
+  --lora_rank 32 \
+  --use_gradient_checkpointing \
+  --task "sft:train"

examples/ltx2/model_training/lora/LTX-2-T2AV.sh

@@ -0,0 +1,19 @@
+accelerate launch examples/ltx2/model_training/train.py \
+  --dataset_base_path data/example_video_dataset/ltx2 \
+  --dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
+  --data_file_keys "video,input_audio" \
+  --extra_inputs "input_audio" \
+  --height 256 \
+  --width 384 \
+  --num_frames 25\
+  --dataset_repeat 100 \
+  --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors,DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
+  --learning_rate 1e-4 \
+  --num_epochs 5 \
+  --remove_prefix_in_ckpt "pipe.dit." \
+  --output_path "./models/train/LTX2-T2AV_lora" \
+  --lora_base_model "dit" \
+  --lora_target_modules "to_k,to_q,to_v,to_out.0" \
+  --lora_rank 32 \
+  --use_gradient_checkpointing \
+  --find_unused_parameters

examples/ltx2/model_training/train.py

@@ -0,0 +1,162 @@
+import torch, os, argparse, accelerate, warnings
+from diffsynth.core import UnifiedDataset
+from diffsynth.core.data.operators import LoadAudioWithTorchaudio, ToAbsolutePath
+from diffsynth.pipelines.wan_video import WanVideoPipeline, ModelConfig
+from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelConfig
+from diffsynth.diffusion import *
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+
+class LTX2TrainingModule(DiffusionTrainingModule):
+    def __init__(
+        self,
+        model_paths=None, model_id_with_origin_paths=None,
+        tokenizer_path=None,
+        trainable_models=None,
+        lora_base_model=None, lora_target_modules="", lora_rank=32, lora_checkpoint=None,
+        preset_lora_path=None, preset_lora_model=None,
+        use_gradient_checkpointing=True,
+        use_gradient_checkpointing_offload=False,
+        extra_inputs=None,
+        fp8_models=None,
+        offload_models=None,
+        device="cpu",
+        task="sft",
+    ):
+        super().__init__()
+        # Warning
+        if not use_gradient_checkpointing:
+            warnings.warn("Gradient checkpointing is detected as disabled. To prevent out-of-memory errors, the training framework will forcibly enable gradient checkpointing.")
+            use_gradient_checkpointing = True
+        
+        # Load models
+        model_configs = self.parse_model_configs(model_paths, model_id_with_origin_paths, fp8_models=fp8_models, offload_models=offload_models, device=device)
+        tokenizer_config = ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized") if tokenizer_path is None else ModelConfig(tokenizer_path)
+        self.pipe = LTX2AudioVideoPipeline.from_pretrained(torch_dtype=torch.bfloat16, device=device, model_configs=model_configs, tokenizer_config=tokenizer_config)
+        self.pipe = self.split_pipeline_units(task, self.pipe, trainable_models, lora_base_model)
+        # Training mode
+        self.switch_pipe_to_training_mode(
+            self.pipe, trainable_models,
+            lora_base_model, lora_target_modules, lora_rank, lora_checkpoint,
+            preset_lora_path, preset_lora_model,
+            task=task,
+        )
+        
+        # Store other configs
+        self.use_gradient_checkpointing = use_gradient_checkpointing
+        self.use_gradient_checkpointing_offload = use_gradient_checkpointing_offload
+        self.extra_inputs = extra_inputs.split(",") if extra_inputs is not None else []
+        self.fp8_models = fp8_models
+        self.task = task
+        self.task_to_loss = {
+            "sft:data_process": lambda pipe, *args: args,
+            "sft": lambda pipe, inputs_shared, inputs_posi, inputs_nega: FlowMatchSFTAudioVideoLoss(pipe, **inputs_shared, **inputs_posi),
+            "sft:train": lambda pipe, inputs_shared, inputs_posi, inputs_nega: FlowMatchSFTAudioVideoLoss(pipe, **inputs_shared, **inputs_posi),
+        }
+        
+    def parse_extra_inputs(self, data, extra_inputs, inputs_shared):
+        for extra_input in extra_inputs:
+            inputs_shared[extra_input] = data[extra_input]
+        return inputs_shared
+    
+    def get_pipeline_inputs(self, data):
+        inputs_posi = {"prompt": data["prompt"]}
+        inputs_nega = {}
+        inputs_shared = {
+            # Assume you are using this pipeline for inference,
+            # please fill in the input parameters.
+            "input_video": data["video"],
+            "height": data["video"][0].size[1],
+            "width": data["video"][0].size[0],
+            "num_frames": len(data["video"]),
+            # Please do not modify the following parameters
+            # unless you clearly know what this will cause.
+            "cfg_scale": 1,
+            "tiled": False,
+            "rand_device": self.pipe.device,
+            "use_gradient_checkpointing": self.use_gradient_checkpointing,
+            "use_gradient_checkpointing_offload": self.use_gradient_checkpointing_offload,
+            "video_patchifier": self.pipe.video_patchifier,
+            "audio_patchifier": self.pipe.audio_patchifier,
+        }
+        inputs_shared = self.parse_extra_inputs(data, self.extra_inputs, inputs_shared)
+        return inputs_shared, inputs_posi, inputs_nega
+    
+    def forward(self, data, inputs=None):
+        if inputs is None: inputs = self.get_pipeline_inputs(data)
+        inputs = self.transfer_data_to_device(inputs, self.pipe.device, self.pipe.torch_dtype)
+        for unit in self.pipe.units:
+            inputs = self.pipe.unit_runner(unit, self.pipe, *inputs)
+        loss = self.task_to_loss[self.task](self.pipe, *inputs)
+        return loss
+
+
+def ltx2_parser():
+    parser = argparse.ArgumentParser(description="Simple example of a training script.")
+    parser = add_general_config(parser)
+    parser = add_video_size_config(parser)
+    parser.add_argument("--tokenizer_path", type=str, default=None, help="Path to tokenizer.")
+    parser.add_argument("--frame_rate", type=float, default=24, help="frame rate of the training videos. If not specified, it will be determined by the dataset.")
+    parser.add_argument("--initialize_model_on_cpu", default=False, action="store_true", help="Whether to initialize models on CPU.")
+    return parser
+
+
+if __name__ == "__main__":
+    parser = ltx2_parser()
+    args = parser.parse_args()
+    accelerator = accelerate.Accelerator(
+        gradient_accumulation_steps=args.gradient_accumulation_steps,
+        kwargs_handlers=[accelerate.DistributedDataParallelKwargs(find_unused_parameters=args.find_unused_parameters)],
+    )
+    dataset = UnifiedDataset(
+        base_path=args.dataset_base_path,
+        metadata_path=args.dataset_metadata_path,
+        repeat=args.dataset_repeat,
+        data_file_keys=args.data_file_keys.split(","),
+        main_data_operator=UnifiedDataset.default_video_operator(
+            base_path=args.dataset_base_path,
+            max_pixels=args.max_pixels,
+            height=args.height,
+            width=args.width,
+            height_division_factor=16,
+            width_division_factor=16,
+            num_frames=args.num_frames,
+            time_division_factor=4,
+            time_division_remainder=1,
+        ),
+        special_operator_map={
+            "input_audio": ToAbsolutePath(args.dataset_base_path) >> LoadAudioWithTorchaudio(duration=float(args.num_frames) / float(args.frame_rate)),
+        }
+    )
+    model = LTX2TrainingModule(
+        model_paths=args.model_paths,
+        model_id_with_origin_paths=args.model_id_with_origin_paths,
+        tokenizer_path=args.tokenizer_path,
+        trainable_models=args.trainable_models,
+        lora_base_model=args.lora_base_model,
+        lora_target_modules=args.lora_target_modules,
+        lora_rank=args.lora_rank,
+        lora_checkpoint=args.lora_checkpoint,
+        preset_lora_path=args.preset_lora_path,
+        preset_lora_model=args.preset_lora_model,
+        use_gradient_checkpointing=args.use_gradient_checkpointing,
+        use_gradient_checkpointing_offload=args.use_gradient_checkpointing_offload,
+        extra_inputs=args.extra_inputs,
+        fp8_models=args.fp8_models,
+        offload_models=args.offload_models,
+        task=args.task,
+        device="cpu" if args.initialize_model_on_cpu else accelerator.device,
+    )
+    model_logger = ModelLogger(
+        args.output_path,
+        remove_prefix_in_ckpt=args.remove_prefix_in_ckpt,
+    )
+    launcher_map = {
+        "sft:data_process": launch_data_process_task,
+        "direct_distill:data_process": launch_data_process_task,
+        "sft": launch_training_task,
+        "sft:train": launch_training_task,
+        "direct_distill": launch_training_task,
+        "direct_distill:train": launch_training_task,
+    }
+    launcher_map[args.task](accelerator, dataset, model, model_logger, args=args)

examples/ltx2/model_training/validate_full/LTX-2-T2AV.py

@@ -0,0 +1,47 @@
+import torch
+from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelConfig
+from diffsynth.utils.data.media_io_ltx2 import write_video_audio_ltx2
+
+vram_config = {
+    "offload_dtype": torch.bfloat16,
+    "offload_device": "cpu",
+    "onload_dtype": torch.bfloat16,
+    "onload_device": "cuda",
+    "preparing_dtype": torch.bfloat16,
+    "preparing_device": "cuda",
+    "computation_dtype": torch.bfloat16,
+    "computation_device": "cuda",
+}
+pipe = LTX2AudioVideoPipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+        ModelConfig(path="./models/train/LTX2-T2AV-full/epoch-4.safetensors", **vram_config),
+    ],
+    tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
+)
+prompt = "A beautiful sunset over the ocean."
+negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
+height, width, num_frames = 512, 768, 121
+video, audio = pipe(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    seed=43,
+    height=height,
+    width=width,
+    num_frames=num_frames,
+    tiled=True,
+    cfg_scale=4.0
+)
+write_video_audio_ltx2(
+    video=video,
+    audio=audio,
+    output_path='ltx2_onestage.mp4',
+    fps=24,
+    audio_sample_rate=24000,
+)

examples/ltx2/model_training/validate_lora/LTX-2-T2AV.py

@@ -0,0 +1,49 @@
+import torch
+from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelConfig
+from diffsynth.utils.data.media_io_ltx2 import write_video_audio_ltx2
+
+vram_config = {
+    "offload_dtype": torch.bfloat16,
+    "offload_device": "cpu",
+    "onload_dtype": torch.bfloat16,
+    "onload_device": "cuda",
+    "preparing_dtype": torch.bfloat16,
+    "preparing_device": "cuda",
+    "computation_dtype": torch.bfloat16,
+    "computation_device": "cuda",
+}
+pipe = LTX2AudioVideoPipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+    ],
+    tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
+)
+pipe.load_lora(pipe.dit, "models/train/LTX2-T2AV_lora/epoch-4.safetensors")
+prompt = "A beautiful sunset over the ocean."
+negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
+height, width, num_frames = 512, 768, 121
+height, width, num_frames = 256, 384, 25
+video, audio = pipe(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    seed=43,
+    height=height,
+    width=width,
+    num_frames=num_frames,
+    tiled=True,
+    cfg_scale=4.0
+)
+write_video_audio_ltx2(
+    video=video,
+    audio=audio,
+    output_path='ltx2_onestage.mp4',
+    fps=24,
+    audio_sample_rate=24000,
+)

examples/ltx2/model_training/validate_lora/LTX-2-T2AV_noaudio.py

@@ -0,0 +1,49 @@
+import torch
+from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelConfig
+from diffsynth.utils.data.media_io_ltx2 import write_video_audio_ltx2
+
+vram_config = {
+    "offload_dtype": torch.bfloat16,
+    "offload_device": "cpu",
+    "onload_dtype": torch.bfloat16,
+    "onload_device": "cuda",
+    "preparing_dtype": torch.bfloat16,
+    "preparing_device": "cuda",
+    "computation_dtype": torch.bfloat16,
+    "computation_device": "cuda",
+}
+pipe = LTX2AudioVideoPipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
+        ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
+    ],
+    tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
+)
+pipe.load_lora(pipe.dit, "models/train/LTX2-T2AV-noaudio_lora/epoch-4.safetensors")
+prompt = "A beautiful sunset over the ocean."
+negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
+height, width, num_frames = 512, 768, 121
+height, width, num_frames = 256, 384, 25
+video, audio = pipe(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    seed=43,
+    height=height,
+    width=width,
+    num_frames=num_frames,
+    tiled=True,
+    cfg_scale=4.0
+)
+write_video_audio_ltx2(
+    video=video,
+    audio=audio,
+    output_path='ltx2_onestage.mp4',
+    fps=24,
+    audio_sample_rate=24000,
+)

examples/ltx2/scripts/split_model_statedicts.py

@@ -0,0 +1,104 @@
+from safetensors.torch import save_file
+from diffsynth import hash_state_dict_keys
+from diffsynth.core import load_state_dict
+from diffsynth.models.model_loader import ModelPool
+
+model_pool = ModelPool()
+state_dict = load_state_dict("models/Lightricks/LTX-2/ltx-2-19b-dev.safetensors")
+
+dit_state_dict = {}
+for name in state_dict:
+    if name.startswith("model.diffusion_model."):
+        new_name = name.replace("model.diffusion_model.", "")
+        if new_name.startswith("audio_embeddings_connector.") or new_name.startswith("video_embeddings_connector."):
+            continue
+        dit_state_dict[name] = state_dict[name]
+
+print(f"dit_state_dict keys hash: {hash_state_dict_keys(dit_state_dict)}")
+save_file(dit_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/transformer.safetensors")
+model_pool.auto_load_model(
+    "models/DiffSynth-Studio/LTX-2-Repackage/transformer.safetensors",
+)
+
+
+video_vae_encoder_state_dict = {}
+for name in state_dict:
+    if name.startswith("vae.encoder."):
+        video_vae_encoder_state_dict[name] = state_dict[name]
+    elif name.startswith("vae.per_channel_statistics."):
+        video_vae_encoder_state_dict[name] = state_dict[name]
+
+save_file(video_vae_encoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/video_vae_encoder.safetensors")
+print(f"video_vae_encoder keys hash: {hash_state_dict_keys(video_vae_encoder_state_dict)}")
+model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/video_vae_encoder.safetensors")
+
+
+video_vae_decoder_state_dict = {}
+for name in state_dict:
+    if name.startswith("vae.decoder."):
+        video_vae_decoder_state_dict[name] = state_dict[name]
+    elif name.startswith("vae.per_channel_statistics."):
+        video_vae_decoder_state_dict[name] = state_dict[name]
+save_file(video_vae_decoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/video_vae_decoder.safetensors")
+print(f"video_vae_decoder keys hash: {hash_state_dict_keys(video_vae_decoder_state_dict)}")
+model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/video_vae_decoder.safetensors")
+
+
+audio_vae_decoder_state_dict = {}
+for name in state_dict:
+    if name.startswith("audio_vae.decoder."):
+        audio_vae_decoder_state_dict[name] = state_dict[name]
+    elif name.startswith("audio_vae.per_channel_statistics."):
+        audio_vae_decoder_state_dict[name] = state_dict[name]
+save_file(audio_vae_decoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/audio_vae_decoder.safetensors")
+print(f"audio_vae_decoder keys hash: {hash_state_dict_keys(audio_vae_decoder_state_dict)}")
+model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/audio_vae_decoder.safetensors")
+
+
+audio_vae_encoder_state_dict = {}
+for name in state_dict:
+    if name.startswith("audio_vae.encoder."):
+        audio_vae_encoder_state_dict[name] = state_dict[name]
+    elif name.startswith("audio_vae.per_channel_statistics."):
+        audio_vae_encoder_state_dict[name] = state_dict[name]
+save_file(audio_vae_encoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/audio_vae_encoder.safetensors")
+print(f"audio_vae_encoder keys hash: {hash_state_dict_keys(audio_vae_encoder_state_dict)}")
+model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/audio_vae_encoder.safetensors")
+
+
+audio_vocoder_state_dict = {}
+for name in state_dict:
+    if name.startswith("vocoder."):
+        audio_vocoder_state_dict[name] = state_dict[name]
+save_file(audio_vocoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/audio_vocoder.safetensors")
+print(f"audio_vocoder keys hash: {hash_state_dict_keys(audio_vocoder_state_dict)}")
+model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/audio_vocoder.safetensors")
+
+
+text_encoder_post_modules_state_dict = {}
+for name in state_dict:
+    if name.startswith("text_embedding_projection."):
+        text_encoder_post_modules_state_dict[name] = state_dict[name]
+    elif name.startswith("model.diffusion_model.video_embeddings_connector."):
+        text_encoder_post_modules_state_dict[name] = state_dict[name]
+    elif name.startswith("model.diffusion_model.audio_embeddings_connector."):
+        text_encoder_post_modules_state_dict[name] = state_dict[name]
+save_file(text_encoder_post_modules_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/text_encoder_post_modules.safetensors")
+print(f"text_encoder_post_modules keys hash: {hash_state_dict_keys(text_encoder_post_modules_state_dict)}")
+model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/text_encoder_post_modules.safetensors")
+
+
+state_dict = load_state_dict("models/Lightricks/LTX-2/ltx-2-19b-distilled.safetensors")
+dit_state_dict = {}
+for name in state_dict:
+    if name.startswith("model.diffusion_model."):
+        new_name = name.replace("model.diffusion_model.", "")
+        if new_name.startswith("audio_embeddings_connector.") or new_name.startswith("video_embeddings_connector."):
+            continue
+        dit_state_dict[name] = state_dict[name]
+
+print(f"dit_state_dict keys hash: {hash_state_dict_keys(dit_state_dict)}")
+save_file(dit_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/transformer_distilled.safetensors")
+model_pool.auto_load_model(
+    "models/DiffSynth-Studio/LTX-2-Repackage/transformer_distilled.safetensors",
+)