Instructions to use LibreYOLO/LibrePRX256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LibreYOLO
How to use LibreYOLO/LibrePRX256 with LibreYOLO:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Diffusers
How to use LibreYOLO/LibrePRX256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LibreYOLO/LibrePRX256", 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 tokenizer/tokenizer.model from LibreYOLO/LibrePRX256: direct link, hf CLI and curl.
- Browser
- Download file 4.24 MB
-
https://huggingface.co/LibreYOLO/LibrePRX256/resolve/main/tokenizer/tokenizer.model
- Command line
-
hf download hf://LibreYOLO/LibrePRX256/tokenizer/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/LibreYOLO/LibrePRX256/resolve/main/tokenizer/tokenizer.model
4.24 MB
- Xet hash:
- 4747d621061ff864406560d79c8c3e355c05f2e88ba30eba88c8d5881d3d220d
- Size of remote file:
- 4.24 MB
- SHA256:
- 61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.