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How to use dherrera-ppm/danielherrera_ymc with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("dherrera-ppm/danielherrera_ymc")
prompt = "Daniel"
image = pipe(prompt).images[0]This is a LoRA for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on Replicate using AI toolkit: https://replicate.com/ostris/flux-dev-lora-trainer/train
You should use Daniel to trigger the image generation.
import replicate
input = {
"prompt": "Daniel",
"lora_weights": "https://huggingface.co/dherrera-ppm/danielherrera_ymc/resolve/main/lora.safetensors"
}
output = replicate.run(
"black-forest-labs/flux-dev-lora",
input=input
)
for index, item in enumerate(output):
with open(f"output_{index}.webp", "wb") as file:
file.write(item.read())
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('dherrera-ppm/danielherrera_ymc', weight_name='lora.safetensors')
image = pipeline('Daniel').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
You can use the community tab to add images that show off what you’ve made with this LoRA.
Base model
black-forest-labs/FLUX.1-dev