Instructions to use smx3/softclub with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use smx3/softclub with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("smx3/softclub") prompt = "-soft club" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from smx3/softclub: direct link, hf CLI and curl.
- Browser
- Download file 550 Bytes
-
https://huggingface.co/smx3/softclub/resolve/main/README.md
- Command line
-
hf download hf://smx3/softclub/README.md
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curl -L -o README.md https://huggingface.co/smx3/softclub/resolve/main/README.md
550 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: undefined
instance_prompt: '-soft club'
license: other
softclub
Model description
fal lora
Trigger words
You should use -soft club to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/krea-2-trainer.