mirror of
https://github.com/modelscope/DiffSynth-Studio.git
synced 2026-03-23 17:38:10 +00:00
update LTX-2.3 doc (#1364)
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@@ -24,88 +24,36 @@ from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelCo
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from diffsynth.utils.data.media_io_ltx2 import write_video_audio_ltx2
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vram_config = {
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"offload_dtype": torch.float8_e5m2,
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"offload_dtype": torch.bfloat16,
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"offload_device": "cpu",
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"onload_dtype": torch.float8_e5m2,
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"onload_device": "cpu",
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"preparing_dtype": torch.float8_e5m2,
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"onload_dtype": torch.bfloat16,
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"onload_device": "cuda",
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"preparing_dtype": torch.bfloat16,
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"preparing_device": "cuda",
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"computation_dtype": torch.bfloat16,
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"computation_device": "cuda",
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}
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"""
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Offical model repo: https://www.modelscope.cn/models/Lightricks/LTX-2
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Repackaged model repo: https://www.modelscope.cn/models/DiffSynth-Studio/LTX-2-Repackage
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For base models of LTX-2, offical checkpoint (with model config ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors"))
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and repackaged checkpoints (with model config ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="*.safetensors")) are both supported.
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We have repackeged the official checkpoints in DiffSynth-Studio/LTX-2-Repackage repo to support separate loading of different submodules,
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and avoid redundant memory usage when users only want to use part of the model.
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"""
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# use the repackaged modelconfig from "DiffSynth-Studio/LTX-2-Repackage" to avoid redundant model loading
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pipe = LTX2AudioVideoPipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
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ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
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ModelConfig(model_id="Lightricks/LTX-2.3", origin_file_pattern="ltx-2.3-22b-dev.safetensors", **vram_config),
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ModelConfig(model_id="Lightricks/LTX-2.3", origin_file_pattern="ltx-2.3-spatial-upscaler-x2-1.0.safetensors", **vram_config),
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],
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tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
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stage2_lora_config=ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled-lora-384.safetensors"),
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vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
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stage2_lora_config=ModelConfig(model_id="Lightricks/LTX-2.3", origin_file_pattern="ltx-2.3-22b-distilled-lora-384.safetensors"),
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)
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# use the following modelconfig if you want to initialize model from offical checkpoints from "Lightricks/LTX-2"
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# pipe = LTX2AudioVideoPipeline.from_pretrained(
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# torch_dtype=torch.bfloat16,
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# device="cuda",
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# model_configs=[
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# ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
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# ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
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# ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
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# ],
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# tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
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# stage2_lora_config=ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled-lora-384.safetensors"),
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# vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
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# )
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prompt = "A girl is very happy, she is speaking: \"I enjoy working with Diffsynth-Studio, it's a perfect framework.\""
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negative_prompt = (
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"blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, "
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"grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, "
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"deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, "
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"wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of "
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"field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent "
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"lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny "
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"valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, "
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"mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, "
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"off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward "
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"pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, "
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"inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
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)
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height, width, num_frames = 512 * 2, 768 * 2, 121
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prompt = "Two cute orange cats, wearing boxing gloves, stand in a boxing ring and fight each other. They are punching each other fast and yelling: 'I will win!'"
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negative_prompt = pipe.default_negative_prompt["LTX-2.3"]
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video, audio = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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seed=43,
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height=height,
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width=width,
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num_frames=num_frames,
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tiled=True,
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use_two_stage_pipeline=True,
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)
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write_video_audio_ltx2(
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video=video,
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audio=audio,
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output_path='ltx2_twostage.mp4',
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fps=24,
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audio_sample_rate=24000,
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height=1024, width=1536, num_frames=121,
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tiled=True, use_two_stage_pipeline=True,
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)
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write_video_audio_ltx2(video=video, audio=audio, output_path='video.mp4', fps=24, audio_sample_rate=pipe.audio_vocoder.output_sampling_rate)
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```
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## Model Overview
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@@ -24,88 +24,36 @@ from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelCo
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from diffsynth.utils.data.media_io_ltx2 import write_video_audio_ltx2
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vram_config = {
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"offload_dtype": torch.float8_e5m2,
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"offload_dtype": torch.bfloat16,
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"offload_device": "cpu",
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"onload_dtype": torch.float8_e5m2,
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"onload_device": "cpu",
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"preparing_dtype": torch.float8_e5m2,
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"onload_dtype": torch.bfloat16,
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"onload_device": "cuda",
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"preparing_dtype": torch.bfloat16,
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"preparing_device": "cuda",
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"computation_dtype": torch.bfloat16,
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"computation_device": "cuda",
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}
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"""
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Offical model repo: https://www.modelscope.cn/models/Lightricks/LTX-2
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Repackaged model repo: https://www.modelscope.cn/models/DiffSynth-Studio/LTX-2-Repackage
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For base models of LTX-2, offical checkpoint (with model config ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors"))
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and repackaged checkpoints (with model config ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="*.safetensors")) are both supported.
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We have repackeged the official checkpoints in DiffSynth-Studio/LTX-2-Repackage repo to support separate loading of different submodules,
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and avoid redundant memory usage when users only want to use part of the model.
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"""
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# use the repackaged modelconfig from "DiffSynth-Studio/LTX-2-Repackage" to avoid redundant model loading
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pipe = LTX2AudioVideoPipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
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ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
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ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
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ModelConfig(model_id="Lightricks/LTX-2.3", origin_file_pattern="ltx-2.3-22b-dev.safetensors", **vram_config),
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ModelConfig(model_id="Lightricks/LTX-2.3", origin_file_pattern="ltx-2.3-spatial-upscaler-x2-1.0.safetensors", **vram_config),
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],
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tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
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stage2_lora_config=ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled-lora-384.safetensors"),
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vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
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stage2_lora_config=ModelConfig(model_id="Lightricks/LTX-2.3", origin_file_pattern="ltx-2.3-22b-distilled-lora-384.safetensors"),
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)
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# use the following modelconfig if you want to initialize model from offical checkpoints from "Lightricks/LTX-2"
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# pipe = LTX2AudioVideoPipeline.from_pretrained(
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# torch_dtype=torch.bfloat16,
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# device="cuda",
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# model_configs=[
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# ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
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# ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
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# ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
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# ],
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# tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
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# stage2_lora_config=ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled-lora-384.safetensors"),
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# vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
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# )
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prompt = "A girl is very happy, she is speaking: \"I enjoy working with Diffsynth-Studio, it's a perfect framework.\""
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negative_prompt = (
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"blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, "
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"grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, "
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"deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, "
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"wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of "
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"field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent "
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"lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny "
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"valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, "
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"mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, "
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"off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward "
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"pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, "
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"inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
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)
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height, width, num_frames = 512 * 2, 768 * 2, 121
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prompt = "Two cute orange cats, wearing boxing gloves, stand in a boxing ring and fight each other. They are punching each other fast and yelling: 'I will win!'"
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negative_prompt = pipe.default_negative_prompt["LTX-2.3"]
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video, audio = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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seed=43,
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height=height,
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width=width,
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num_frames=num_frames,
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tiled=True,
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use_two_stage_pipeline=True,
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)
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write_video_audio_ltx2(
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video=video,
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audio=audio,
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output_path='ltx2_twostage.mp4',
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fps=24,
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audio_sample_rate=24000,
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height=1024, width=1536, num_frames=121,
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tiled=True, use_two_stage_pipeline=True,
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)
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write_video_audio_ltx2(video=video, audio=audio, output_path='video.mp4', fps=24, audio_sample_rate=pipe.audio_vocoder.output_sampling_rate)
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```
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## 模型总览
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