Instructions to use BoghdadyJR/Qwen_roco_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BoghdadyJR/Qwen_roco_final with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BoghdadyJR/Qwen_roco_final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from BoghdadyJR/Qwen_roco_final: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/BoghdadyJR/Qwen_roco_final/resolve/main/tokenizer.json
- Command line
-
hf download hf://BoghdadyJR/Qwen_roco_final/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/BoghdadyJR/Qwen_roco_final/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- edc9debc76103ad22bdcc5c669d8d7b4815e3dd80a79371c91aed6b083a83ae4
- Size of remote file:
- 11.4 MB
- SHA256:
- 00ff1d43b119596534f778ecc067f5b457d2ce2fe2665ab12fe7a8705fda3437
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.