Instructions to use mlc-ai/CodeLlama-7b-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-7b-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_2.bin from mlc-ai/CodeLlama-7b-Python-hf-q4f16_1-MLC: direct link, hf CLI and curl.
- Browser
- Download file 45.1 MB
-
https://huggingface.co/mlc-ai/CodeLlama-7b-Python-hf-q4f16_1-MLC/resolve/main/params_shard_2.bin
- Command line
-
hf download hf://mlc-ai/CodeLlama-7b-Python-hf-q4f16_1-MLC/params_shard_2.bin
-
curl -L -o params_shard_2.bin https://huggingface.co/mlc-ai/CodeLlama-7b-Python-hf-q4f16_1-MLC/resolve/main/params_shard_2.bin
45.1 MB
- Xet hash:
- 47bf5cfdc40923ed0684472affeb9ee26e586f9258c46a1dee499af331ce05f0
- Size of remote file:
- 45.1 MB
- SHA256:
- 0e29275bf53d72c646ec1eb1f222aa9cfa7753d075a48cfed271c7ab948b9c9c
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