Instructions to use mlc-ai/CodeLlama-70b-Python-hf-q4f16_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-q4f16_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_128.bin from mlc-ai/CodeLlama-70b-Python-hf-q4f16_1-MLC: direct link, hf CLI and curl.
- Browser
- Download file 117 MB
-
https://huggingface.co/mlc-ai/CodeLlama-70b-Python-hf-q4f16_1-MLC/resolve/main/params_shard_128.bin
- Command line
-
hf download hf://mlc-ai/CodeLlama-70b-Python-hf-q4f16_1-MLC/params_shard_128.bin
-
curl -L -o params_shard_128.bin https://huggingface.co/mlc-ai/CodeLlama-70b-Python-hf-q4f16_1-MLC/resolve/main/params_shard_128.bin
117 MB
- Xet hash:
- cf5cc1f062899ff7d5f5337a291c34f94364928ba88f5864598df0e96bb3acbb
- Size of remote file:
- 117 MB
- SHA256:
- 07548a51370df4444f6249ddbf1c21a5efa8dc38a66dbba8915932fe9af99fc3
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