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/0.0.1 from nvidia/OpenMath-CodeLlama-70b-Python: direct link, hf CLI and curl.
- Browser
- Download file 58.7 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-70b-Python/resolve/643e72d21f050df2b4f84cfc82da215db4433b02/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/0.0.1
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-70b-Python@643e72d21f050df2b4f84cfc82da215db4433b02/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/0.0.1
-
curl -L -o 0.0.1 https://huggingface.co/nvidia/OpenMath-CodeLlama-70b-Python/resolve/643e72d21f050df2b4f84cfc82da215db4433b02/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/0.0.1
58.7 MB
- Xet hash:
- 391a3a1cd770796f540c894393713d0997cabe34e09730c00d5d674c62e69b1f
- Size of remote file:
- 58.7 MB
- SHA256:
- 195d78e4201ef723e5d299e4fc7da84c28dca2ee1b13dd317869410ea13bdd4a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.