Instructions to use mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC with MLC-LLM:
# 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
- Notebooks
- Google Colab
- Kaggle
Download params_shard_13.bin from mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC: direct link, hf CLI and curl.
- Browser
- Download file 117 MB
-
https://huggingface.co/mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC/resolve/main/params_shard_13.bin
- Command line
-
hf download hf://mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC/params_shard_13.bin
-
curl -L -o params_shard_13.bin https://huggingface.co/mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC/resolve/main/params_shard_13.bin
117 MB
- Xet hash:
- 70bce888845d00a3829bf436f8e21483b6a5b01b8dd3a57f0fcca2cdba5779e5
- Size of remote file:
- 117 MB
- SHA256:
- 939b9a2fea44013d0247da3a84b47933de1b50db07e1cfda0a69c039242a06ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.