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LongCat Image Edit Turbo DF11

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KindUNetBase modelmeituan-longcat/LongCat-Image-Edit-TurboVersionmodelDgrade

Model source

Kind
UNet
File size
8.29 GB
Base model
meituan-longcat/LongCat-Image-Edit-Turbo
Version
vmodel
Updated
Oct 14, 2026
Downloads
28
Source
Hugging Face

Source description

For more information (including how to compress models yourself), check out https://huggingface.co/DFloat11 and https://github.com/LeanModels/DFloat11

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.

How to Use

diffusers

import torch
from diffusers import LongCatImageEditPipeline, LongCatImageTransformer2DModel

# for newer versions of `transformers`, it seems that from transformers.initialization import no_init_weights is required instead
from transformers.modeling_utils import no_init_weights

with no_init_weights():
    transformer = LongCatImageTransformer2DModel.from_config(
        LongCatImageTransformer2DModel.load_config(
            "meituan-longcat/LongCat-Image-Edit-Turbo", subfolder="transformer"
        ),
        torch_dtype=torch.bfloat16
    ).to(torch.bfloat16)
DFloat11Model.from_pretrained(
    "mingyi456/LongCat-Image-Edit-Turbo-DF11",
    device="cpu",
    bfloat16_model=transformer,
)
pipe = LongCatImageEditPipeline.from_pretrained(
    "meituan-longcat/LongCat-Image-Edit-Turbo",
    transformer=transformer, 
    torch_dtype=torch.bfloat16
)
DFloat11Model.from_pretrained(
    "mingyi456/Qwen2.5-VL-7B-Instruct-DF11",
    device="cpu",
    bfloat16_model=pipe.text_encoder,
)
pipe.enable_model_cpu_offload()
img = Image.open('assets/test.png').convert('RGB')
prompt = '将猫变成狗'
image = pipe(
    img,
    prompt,
    negative_prompt='',
    guidance_scale=1.0,
    num_inference_steps=8,
    num_images_per_prompt=1,
    generator=torch.Generator("cpu").manual_seed(43)
).images[0]
image.save('image longcat-image-edit.png')

ComfyUI

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.

Compression details

This is the pattern_dict for compression:

pattern_dict = {
    r"transformer_blocks\.\d+": (
        "norm1.linear",
        "norm1_context.linear",
        "attn.to_q",
        "attn.to_k",
        "attn.to_v",
        "attn.to_out.0",
        "attn.add_q_proj",
        "attn.add_k_proj",
        "attn.add_v_proj",
        "attn.to_add_out",
        "ff.net.0.proj",
        "ff.net.2",
        "ff_context.net.0.proj",
        "ff_context.net.2",
    ),
    r"single_transformer_blocks\.\d+": (
        "norm.linear",
        "proj_mlp",
        "proj_out",
        "attn.to_q",
        "attn.to_k",
        "attn.to_v",
    ),
}

Sources

1 source
Hugging FacePrimaryVersion e7306f6c225957dbc1d8392c2ac79e04cbcb046a
huggingface.co/mingyi456/LongCat-Image-Edit-Turbo-DF11/tree/e7306f6c225957dbc1d8392c2ac79e04cbcb046a

Verified Sep 22

Model artifacts

1 artifact

model.safetensors

safetensors · 8.29 GB · SHA-256 ddb9ffb5b334…50b8 · Hugging Face

Download

Source excerpts

3 excerpts

--- license: apache-2.0 language: - en - zh base_model: - meituan-longcat/LongCat-Image-Edit-Turbo base_model_relation: quantized pipeline_tag: image-text-to-image library_name: diffusers tags: - diffusion-single-file --- For more information (including how to compress models yourself), check out https://huggingface.co/DFloat11 and https://github.com/LeanModels/DFloat11 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. ### How to Use #### `diffusers` ```python import torch from diffusers import LongCatImageEditPipeline, LongCatImageTransformer2DModel # for newer versions of `transformers`, it seems that from transformers.initialization import no_init_weights is required instead from transformers.modeling_utils import no_init_weights with no_init_weights(): transformer = LongCatImageTransformer2DModel.from_config( LongCatImageTransformer2DModel.load_config( "meituan-longcat/LongCat-Image-Edit-Turbo", subfolder="transformer" ), torch_dtype=torch.bfloat16 ).to(torch.bfloat16) DFloat11Model.from_pretrained( "mingyi456/LongCat-Image-Edit-Turbo-DF11", device="cpu", bfloat16_model=transformer, ) pipe = LongCatImageEditPipeline.from_pretrained( "meituan-longcat/LongCat-Image-Edit-Turbo", transformer=transformer, torch_dtype=torch.bfloat16 ) DFloat11Model.from_pretrained( "mingyi456/Qwen2.5-VL-7B-Instruct-DF11", device="cpu", bfloat16_model=pipe.text_encoder, ) pipe.enable_model_cpu_offload() img = Image.open('assets/test.png').convert('RGB') prompt = '将猫变成狗' image = pipe( img, prompt, negative_prompt='', guidance_scale=1.0, num_inference_steps=8, num_images_per_prompt=1, generator=torch.Generator("cpu").manual_seed(43) ).images[0] image.save('image longcat-image-edit.png') ``` #### ComfyUI 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. ### Compression details This is the `pattern_dict` for compression: ```python pattern_dict = { r"transformer_blocks\.\d+": ( "norm1.linear", "norm1_context.linear", "attn.to_q", "attn.to_k", "attn.to_v", "attn.to_out.0", "attn.add_q_proj", "attn.add_k_proj", "attn.add_v_proj", "attn.to_add_out", "ff.net.0.proj", "ff.net.2", "ff_c...

Source context: 28 downloads · 0 likes · Pipeline image-text-to-image · Library diffusers · Repo mingyi456/LongCat-Image-Edit-Turbo-DF11

Source context: 30 downloads · 0 likes · Pipeline image-text-to-image · Library diffusers · Repo mingyi456/LongCat-Image-Edit-Turbo-DF11