Instructions to use nvidia/OpenMath-CodeLlama-34b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-34b-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/13.0.0 from nvidia/OpenMath-CodeLlama-34b-Python: direct link, hf CLI and curl.
- Browser
- Download file 45.1 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/13.0.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/13.0.0
-
curl -L -o 13.0.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/13.0.0
45.1 MB
- Xet hash:
- 979d8195c5bd745c84e6e81c96640ce3d841ccce9aa10ff71e58cf5b38a9d395
- Size of remote file:
- 45.1 MB
- SHA256:
- edfb77d2753888562d6e5c31d3143de333d86d520be0353631ba228da6c11d78
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.