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_121.bin from mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC: direct link, hf CLI and curl.
- Browser
- Download file 235 MB
-
https://huggingface.co/mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC/resolve/main/params_shard_121.bin
- Command line
-
hf download hf://mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC/params_shard_121.bin
-
curl -L -o params_shard_121.bin https://huggingface.co/mlc-ai/CodeLlama-70b-Python-hf-q4f32_1-MLC/resolve/main/params_shard_121.bin
235 MB
- Xet hash:
- 18ede5166b905263eda636e9b0ee849911c821cd7a5f9f68f4cf9835e6b41f7e
- Size of remote file:
- 235 MB
- SHA256:
- f6454ab13e80362c70a9a7bc940f6fc37be9b7cb98af4999f229ed9a29122172
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.