LongCat Image Edit Turbo DF11
For more information (including how to compress models yourself), check out and
Fuente del modelo
- Tipo
- UNet
- Tamaño del archivo
- 8,29 GB
- Modelo base
- meituan-longcat/LongCat-Image-Edit-Turbo
- Versión
- vmodel
- Actualizado
- 14 oct 2026
- Descargas
- 28
- Fuente
- Hugging Face
Descripción de la fuente
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",
),
}
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 22 sept
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- 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
