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_fc1.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/643e72d21f050df2b4f84cfc82da215db4433b02/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.weight/.zarray
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-70b-Python@643e72d21f050df2b4f84cfc82da215db4433b02/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.weight/.zarray
-
curl -L -o .zarray https://huggingface.co/nvidia/OpenMath-CodeLlama-70b-Python/resolve/643e72d21f050df2b4f84cfc82da215db4433b02/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.weight/.zarray
259 Bytes
- Xet hash:
- bb1dddada1b5f181ca7e0bd3d3931af5fc6080cabfb027eaa26600a7a92c9aa3
- Size of remote file:
- 259 Bytes
- SHA256:
- c235e85430ddca93cca4f2c8a8863e65d1ca31efcac59269fa00d529f5a70221
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