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/0.0.5 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/3249d1fca2b89c7549d032dd74c185041a75956e/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/0.0.5
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python@3249d1fca2b89c7549d032dd74c185041a75956e/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/0.0.5
-
curl -L -o 0.0.5 https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/3249d1fca2b89c7549d032dd74c185041a75956e/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/0.0.5
45.1 MB
- Xet hash:
- c170d4e045c049befa9e42a87687349732b53a3fb15e36ca0680bc4689836395
- Size of remote file:
- 45.1 MB
- SHA256:
- 9837fc8737853d7aefce79f71fb664aee58181cbc2b7a613b4c25f44fd3bdba2
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