update docs

This commit is contained in:
mi804
2026-02-26 11:10:00 +08:00
parent 8d8bfc7f54
commit f48662e863
9 changed files with 258 additions and 15 deletions

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@@ -32,7 +32,9 @@ We believe that a well-developed open-source code framework can lower the thresh
> DiffSynth-Studio has undergone major version updates, and some old features are no longer maintained. If you need to use old features, please switch to the [last historical version](https://github.com/modelscope/DiffSynth-Studio/tree/afd101f3452c9ecae0c87b79adfa2e22d65ffdc3) before the major version update.
> Currently, the development personnel of this project are limited, with most of the work handled by [Artiprocher](https://github.com/Artiprocher). Therefore, the progress of new feature development will be relatively slow, and the speed of responding to and resolving issues is limited. We apologize for this and ask developers to understand.
- **February 10, 2026** Added inference and training support for the LTX-2 audio-video generation model. See the documentation for details.
- **February 26, 2026** Added full and lora training support for the LTX-2 audio-video generation model. See the [documentation](/docs/en/Model_Details/LTX-2.md) for details.
- **February 10, 2026** Added inference support for the LTX-2 audio-video generation model. See the [documentation](/docs/en/Model_Details/LTX-2.md) for details. Support for model training will be implemented in the future.
- **February 2, 2026** The first document of the Research Tutorial series is now available, guiding you through training a small 0.1B text-to-image model from scratch. For details, see the [documentation](/docs/en/Research_Tutorial/train_from_scratch.md) and [model](https://modelscope.cn/models/DiffSynth-Studio/AAAMyModel). We hope DiffSynth-Studio can evolve into a more powerful training framework for Diffusion models.
@@ -557,12 +559,26 @@ vram_config = {
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
"""
Offical model repo: https://www.modelscope.cn/models/Lightricks/LTX-2
Repackaged model repo: https://www.modelscope.cn/models/DiffSynth-Studio/LTX-2-Repackage
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"))
and repackaged checkpoints (with model config ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="*.safetensors")) are both supported.
We have repackeged the official checkpoints in DiffSynth-Studio/LTX-2-Repackage repo to support separate loading of different submodules,
and avoid redundant memory usage when users only want to use part of the model.
"""
# use the repackaged modelconfig from "DiffSynth-Studio/LTX-2-Repackage" to avoid redundant model loading
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="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"),
@@ -570,6 +586,20 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
)
# use the following modelconfig if you want to initialize model from offical checkpoints from "Lightricks/LTX-2"
# 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="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.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"),
# stage2_lora_config=ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled-lora-384.safetensors"),
# vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
# )
prompt = "A girl is very happy, she is speaking: \"I enjoy working with Diffsynth-Studio, it's a perfect framework.\""
negative_prompt = (
"blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, "