Instructions to use shaharh/puppet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shaharh/puppet 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("shaharh/puppet") prompt = "puppet style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from shaharh/puppet: direct link, hf CLI and curl.
- Browser
- Download file 551 Bytes
-
https://huggingface.co/shaharh/puppet/resolve/main/README.md
- Command line
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hf download hf://shaharh/puppet/README.md
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curl -L -o README.md https://huggingface.co/shaharh/puppet/resolve/main/README.md
551 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: undefined
instance_prompt: puppet style
license: other
puppet
Model description
Trigger words
You should use puppet style 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/flux-krea-trainer.