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Support Anima (#1317)
* support Anima Co-authored-by: mi804 <1576993271@qq.com>
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57
README_zh.md
57
README_zh.md
@@ -32,6 +32,9 @@ DiffSynth 目前包括两个开源项目:
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> DiffSynth-Studio 经历了大版本更新,部分旧功能已停止维护,如需使用旧版功能,请切换到大版本更新前的[最后一个历史版本](https://github.com/modelscope/DiffSynth-Studio/tree/afd101f3452c9ecae0c87b79adfa2e22d65ffdc3)。
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> 目前本项目的开发人员有限,大部分工作由 [Artiprocher](https://github.com/Artiprocher) 负责,因此新功能的开发进展会比较缓慢,issue 的回复和解决速度有限,我们对此感到非常抱歉,请各位开发者理解。
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- **2026年3月2日** 新增对[Anima](https://modelscope.cn/models/circlestone-labs/Anima)的支持,详见[文档](docs/zh/Model_Details/Anima.md)。这是一个有趣的动漫风格图像生成模型,我们期待其后续的模型更新。
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- **2026年2月26日** 新增对[LTX-2](https://www.modelscope.cn/models/Lightricks/LTX-2)音视频生成模型全量微调与LoRA训练支持,详见[文档](docs/zh/Model_Details/LTX-2.md)。
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- **2026年2月10日** 新增对[LTX-2](https://www.modelscope.cn/models/Lightricks/LTX-2)音视频生成模型的推理支持,详见[文档](docs/zh/Model_Details/LTX-2.md),后续将推进模型训练的支持。
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@@ -343,6 +346,60 @@ FLUX.2 的示例代码位于:[/examples/flux2/](/examples/flux2/)
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</details>
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#### Anima: [/docs/zh/Model_Details/Anima.md](/docs/zh/Model_Details/Anima.md)
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<details>
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<summary>快速开始</summary>
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运行以下代码可以快速加载 [circlestone-labs/Anima](https://www.modelscope.cn/models/circlestone-labs/Anima) 模型并进行推理。显存管理已启动,框架会自动根据剩余显存控制模型参数的加载,最低 8G 显存即可运行。
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```python
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from diffsynth.pipelines.anima_image import AnimaImagePipeline, ModelConfig
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import torch
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vram_config = {
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"offload_dtype": "disk",
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"offload_device": "disk",
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"onload_dtype": "disk",
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"onload_device": "disk",
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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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pipe = AnimaImagePipeline.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="circlestone-labs/Anima", origin_file_pattern="split_files/diffusion_models/anima-preview.safetensors", **vram_config),
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ModelConfig(model_id="circlestone-labs/Anima", origin_file_pattern="split_files/text_encoders/qwen_3_06b_base.safetensors", **vram_config),
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ModelConfig(model_id="circlestone-labs/Anima", origin_file_pattern="split_files/vae/qwen_image_vae.safetensors", **vram_config),
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],
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tokenizer_config=ModelConfig(model_id="Qwen/Qwen3-0.6B", origin_file_pattern="./"),
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tokenizer_t5xxl_config=ModelConfig(model_id="stabilityai/stable-diffusion-3.5-large", origin_file_pattern="tokenizer_3/"),
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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 = "Masterpiece, best quality, solo, long hair, wavy hair, silver hair, blue eyes, blue dress, medium breasts, dress, underwater, air bubble, floating hair, refraction, portrait."
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negative_prompt = "worst quality, low quality, monochrome, zombie, interlocked fingers, Aissist, cleavage, nsfw,"
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image = pipe(prompt, seed=0, num_inference_steps=50)
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image.save("image.jpg")
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```
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</details>
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<details>
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<summary>示例代码</summary>
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Anima 的示例代码位于:[/examples/anima/](/examples/anima/)
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|模型 ID|推理|低显存推理|全量训练|全量训练后验证|LoRA 训练|LoRA 训练后验证|
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|-|-|-|-|-|-|-|
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|[circlestone-labs/Anima](https://www.modelscope.cn/models/circlestone-labs/Anima)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/anima/model_inference/anima-preview.py)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/anima/model_inference_low_vram/anima-preview.py)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/anima/model_training/full/anima-preview.sh)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/anima/model_training/validate_full/anima-preview.py)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/anima/model_training/lora/anima-preview.sh)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/anima/model_training/validate_lora/anima-preview.py)|
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</details>
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#### Qwen-Image: [/docs/zh/Model_Details/Qwen-Image.md](/docs/zh/Model_Details/Qwen-Image.md)
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<details>
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