Instructions to use LucasFang/PUMA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LucasFang/PUMA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LucasFang/PUMA", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download clip-vit-large-patch14/tokenizer.json from LucasFang/PUMA: direct link, hf CLI and curl.
- Browser
- Download file 2.22 MB
-
https://huggingface.co/LucasFang/PUMA/resolve/main/clip-vit-large-patch14/tokenizer.json
- Command line
-
hf download hf://LucasFang/PUMA/clip-vit-large-patch14/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/LucasFang/PUMA/resolve/main/clip-vit-large-patch14/tokenizer.json
2.22 MB
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