Instructions to use nvidia/OpenMath-CodeLlama-7b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-7b-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/18.1.0 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 25.2 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/18.1.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python@e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/18.1.0
-
curl -L -o 18.1.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/18.1.0
25.2 MB
- Xet hash:
- 8122ed86868db1087689610230a710099b6d9d8c54eef86a3065dd6bbc51ab23
- Size of remote file:
- 25.2 MB
- SHA256:
- 5e016c9f20649171b1b4ec4a5c1af1e8299cafad99acc40abad7e452690f1945
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