Instructions to use EVA787797/78778 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EVA787797/78778 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("EVA787797/78778") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 742 Bytes
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tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: '-'
output:
url: images/téléchargement (2).jfif
base_model:
- black-forest-labs/FLUX.1-dev
instance_prompt: femme
license: afl-3.0
language:
- fr
- an
- en
- it
- ja
---
# pipeline.py __init_
<Gallery />
## Model description

## Trigger words
You should use `femme` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/EVA787797/78778/tree/main) them in the Files & versions tab. |