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_fc1.layer_norm_weight/46.0 from nvidia/OpenMath-CodeLlama-34b-Python: direct link, hf CLI and curl.
- Browser
- Download file 16.4 kB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/46.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python@f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/46.0
-
curl -L -o 46.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/46.0
16.4 kB
- Xet hash:
- b4160042511d0848b7d61641a521473d45a66244000697a8e1a6562fca062301
- Size of remote file:
- 16.4 kB
- SHA256:
- bd2a370e0c5817ca13539ea3f59169c54180519ac71ac7ac20a1cfaa4b4500c8
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