Instructions to use riteshkr/quantized_llama-3.2-11B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use riteshkr/quantized_llama-3.2-11B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("riteshkr/quantized_llama-3.2-11B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from riteshkr/quantized_llama-3.2-11B: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/riteshkr/quantized_llama-3.2-11B/resolve/main/tokenizer.json
- Command line
-
hf download hf://riteshkr/quantized_llama-3.2-11B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/riteshkr/quantized_llama-3.2-11B/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- bfd91a313ec19d3681e6b63a8890f4908a53bddb371077e2185c072834d2eca6
- Size of remote file:
- 17.2 MB
- SHA256:
- 9816d43bd5347d64bccc66b7710947fb18e9818cc660215b1462061d4a44e449
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