Instructions to use nvidia/OpenMath-CodeLlama-70b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-70b-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/.zarray from nvidia/OpenMath-CodeLlama-70b-Python: direct link, hf CLI and curl.
- Browser
- Download file 259 Bytes
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-70b-Python/resolve/caf5674e1eb01122ec306bae5a957176c7cd5b04/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/.zarray
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-70b-Python@caf5674e1eb01122ec306bae5a957176c7cd5b04/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/.zarray
-
curl -L -o .zarray https://huggingface.co/nvidia/OpenMath-CodeLlama-70b-Python/resolve/caf5674e1eb01122ec306bae5a957176c7cd5b04/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/.zarray
259 Bytes
- Xet hash:
- 5fd87e6b0659a45c855b2570d4e033a31e05b8c5a0c85925b2308d7fe3f2b0b8
- Size of remote file:
- 259 Bytes
- SHA256:
- 8dd86e680d422cb0e9cc7c265b72af0aaf9c6294ad466f96fb55a441f61b3bc9
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