huggingface / huggingface/diffusers

FLUX.1-dev FP8 Example Code Cleanup

Abierto
#9,690 8 comentarios 0 reacciones 0 asignados Ver en GitHub
Lenguaje dominante
Python
Estrellas
34.5k
Forks
7.3k
Merge medio
3 d 3 h
PR fusionados (30 d)
91

Descripción

I was looking at the [FLUX.1-dev FP8 example code](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux#single-file-loading-for-the-fluxtransformer2dmodel) in the documentation and noticed some unnecessary imports and variable declarations, which make it appear longer and cluttered. Here is the shorter version of the code I'm currently using. Please note that I'm not an expert, just trying to make it easier for anyone else looking to run the code.

```
import torch
from diffusers import FluxTransformer2DModel, FluxPipeline
from transformers import T5EncoderModel
from optimum.quanto import quantize, qfloat8, freeze

bfl_repo = "black-forest-labs/FLUX.1-dev"

transformer = FluxTransformer2DModel.from_single_file("https://huggingface.co/Kijai/flux-fp8/blob/main/flux1-dev-fp8.safetensors", torch_dtype=torch.bfloat16)
quantize(transformer, weights=qfloat8)
freeze(transformer)

text_encoder_2 = T5EncoderModel.from_pretrained(bfl_repo, subfolder="text_encoder_2", torch_dtype=torch.bfloat16)
quantize(text_encoder_2, weights=qfloat8)
freeze(text_encoder_2)

pipe = FluxPipeline.from_pretrained(bfl_repo, transformer=transformer, text_encoder_2=text_encoder_2, torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload()

prompt = "A cat holding a sign that says hello world"
image = pipe(
prompt,
generator=torch.Generator("cpu").manual_seed(0)
).images[0]

image.save("flux-dev-fp8.png")
```

Optimizations made:
Removed unnecessary code and reduced the line count from 32 to 26.

Guía de contribución

Abrir la guía de contribución

Línea de trabajo

Start with the linked FLUX.1-dev FP8 example in the Diffusers documentation and compare it with the shorter code shown in this issue. Remove the unnecessary imports and variable declarations while preserving the example's behavior, then verify that the documentation code remains runnable.

Escrito por el modelo de indexación a partir del texto del issue.

Evaluación

Stack tecnológico
python, pytorch
Área
documentation
Tipo de issue
Documentación
Dificultad
1/5
Tiempo estimado
1-3 horas
Estado de actividad
Estancado
Claridad
Bien especificado
Aptitud para principiantes
45/100

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