Instructions to use Jonjew/RachelCook with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/RachelCook 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("Jonjew/RachelCook") prompt = "<lora:Rachel_Cook_Flux:1> beautiful detailed photograph, brown hair cascading over her shoulders, wearing a boatneck dress, standing in a cafe, looking at the viewer, smile" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 709 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: >-
<lora:Rachel_Cook_Flux:1> beautiful detailed photograph, brown hair
cascading over her shoulders, wearing a boatneck dress, standing in a cafe,
looking at the viewer, smile
output:
url: images/00015-288266579.jpeg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
license: unknown
---
# Rachel Cook
<Gallery />
## Model description
FROM https://civitai.com/models/944361/rachel-cook-flux
Strength 1
## Download model
Weights for this model are available in Safetensors format.
[Download](/Jonjew/RachelCook/tree/main) them in the Files & versions tab.
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