What is Diffusers?
1. Create a virtual env
python3 -m venv fluxtest
source fluxtest/bin/activate
2. Login to Hugging Face via CLI
https://huggingface.co/docs/huggingface_hub/main/en/guides/cli
pip install -U "huggingface_hub[cli]"
huggingface-cli login
3. Install packages
pip install torch==2.3.1
pip install git+https://github.com/huggingface/diffusers.git
pip install transformers==4.43.3 sentencepiece==0.2.0 accelerate==0.33.0 protobuf==5
4. Run a python script
import torch
from diffusers import FluxPipeline
import diffusers
_flux_rope = diffusers.models.transformers.transformer_flux.rope
def new_flux_rope(pos: torch.Tensor, dim: int, theta: int) -> torch.Tensor:
assert dim % 2 == 0, "The dimension must be even."
if pos.device.type == "mps":
return _flux_rope(pos.to("cpu"), dim, theta).to(device=pos.device)
else:
return _flux_rope(pos, dim, theta)
diffusers.models.transformers.transformer_flux.rope = new_flux_rope
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", revision='refs/pr/1', torch_dtype=torch.bfloat16).to("mps")
prompt = "japanese girl, photo-realistic"
out = pipe(
prompt=prompt,
guidance_scale=0.,
height=1024,
width=1024,
num_inference_steps=4,
max_sequence_length=256,
).images[0]
out.save("image.png")
python image.py
output
got the script from lucataco!
Run Flux.1 on M3 Mac with ComfyUI