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--- |
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license: apache-2.0 |
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language: |
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- en |
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- zh |
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base_model: |
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- meituan-longcat/LongCat-Image-Edit |
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base_model_relation: quantized |
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pipeline_tag: text-to-image |
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library_name: diffusers |
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tags: |
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- diffusion-single-file |
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--- |
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For more information (including how to compress models yourself), check out https://huggingface.co/DFloat11 and https://github.com/LeanModels/DFloat11 |
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Feel free to request for other models for compression as well (for either the `diffusers` library, ComfyUI, or any other model), although models that use architectures which are unfamiliar to me might be more difficult. |
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### How to Use |
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#### `diffusers` |
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```python |
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import torch |
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from diffusers import LongCatImageEditPipeline, LongCatImageTransformer2DModel |
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from transformers.modeling_utils import no_init_weights |
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with no_init_weights(): |
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transformer = LongCatImageTransformer2DModel.from_config( |
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LongCatImageTransformer2DModel.load_config( |
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"meituan-longcat/LongCat-Image-Edit", subfolder="transformer" |
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), |
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torch_dtype=torch.bfloat16 |
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).to(torch.bfloat16) |
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DFloat11Model.from_pretrained( |
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"mingyi456/LongCat-Image-Edit-DF11", |
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device="cpu", |
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bfloat16_model=transformer, |
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) |
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pipe = LongCatImageEditPipeline.from_pretrained( |
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"meituan-longcat/LongCat-Image-Edit", |
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transformer=transformer, |
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torch_dtype=torch.bfloat16 |
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) |
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DFloat11Model.from_pretrained( |
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"mingyi456/Qwen2.5-VL-7B-Instruct-DF11", |
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device="cpu", |
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bfloat16_model=pipe.text_encoder, |
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) |
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pipe.enable_model_cpu_offload() |
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img = Image.open('assets/test.png').convert('RGB') |
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prompt = '将猫变成狗' |
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image = pipe( |
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img, |
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prompt, |
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negative_prompt='', |
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guidance_scale=4.5, |
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num_inference_steps=50, |
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num_images_per_prompt=1, |
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generator=torch.Generator("cpu").manual_seed(43) |
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).images[0] |
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image.save('image longcat-image-edit.png') |
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``` |
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#### ComfyUI |
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Currently, this model is not supported natively in ComfyUI. Do let me know if it receives native support, and I will get to supporting it. |
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### Compression details |
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This is the `pattern_dict` for compression: |
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```python |
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pattern_dict = { |
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r"transformer_blocks\.\d+": ( |
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"norm1.linear", |
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"norm1_context.linear", |
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"attn.to_q", |
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"attn.to_k", |
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"attn.to_v", |
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"attn.to_out.0", |
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"attn.add_q_proj", |
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"attn.add_k_proj", |
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"attn.add_v_proj", |
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"attn.to_add_out", |
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"ff.net.0.proj", |
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"ff.net.2", |
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"ff_context.net.0.proj", |
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"ff_context.net.2", |
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), |
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r"single_transformer_blocks\.\d+": ( |
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"norm.linear", |
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"proj_mlp", |
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"proj_out", |
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"attn.to_q", |
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"attn.to_k", |
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"attn.to_v", |
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), |
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} |
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``` |
