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.mlp.linear_fc2.weight/16.0.0 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 22.5 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/16.0.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python@e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/16.0.0
-
curl -L -o 16.0.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/16.0.0
22.5 MB
- Xet hash:
- 0c9ac367c3ed3c2989df936971a6c5f58fa65e65e9a1635a6a9dc8b25eb4957a
- Size of remote file:
- 22.5 MB
- SHA256:
- 776574f06c171850dee9a7d38c5ec73d3ab6adf5fdb6654c25bd63bb81bb6956
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