Instructions to use nvidia/OpenMath-CodeLlama-34b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-34b-Python with NeMo:
# tag did not correspond to a valid NeMo domain.
- Notebooks
- Google Colab
- Kaggle
Download nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/11.0.0 from nvidia/OpenMath-CodeLlama-34b-Python: direct link, hf CLI and curl.
- Browser
- Download file 21 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/3249d1fca2b89c7549d032dd74c185041a75956e/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/11.0.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python@3249d1fca2b89c7549d032dd74c185041a75956e/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/11.0.0
-
curl -L -o 11.0.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/3249d1fca2b89c7549d032dd74c185041a75956e/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/11.0.0
21 MB
- Xet hash:
- 27eda145ce5014c83d86c870588fd9837560409029d66367b0220de6bc76d57c
- Size of remote file:
- 21 MB
- SHA256:
- 1a6b2b840e17f560f3fbf48759da259d0633367d30d17a3e206d8d6436d236d6
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