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.self_attention.linear_proj.weight/0.0.2 from nvidia/OpenMath-CodeLlama-34b-Python: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_proj.weight/0.0.2
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python/nemo_model/model_weights/model.decoder.layers.self_attention.linear_proj.weight/0.0.2
-
curl -L -o 0.0.2 https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_proj.weight/0.0.2
16.8 MB
- Xet hash:
- 7121f8c2b2e500e94b6f7a5efa2e172eefaf7e14c329ab343368d7f1a3f4ee78
- Size of remote file:
- 16.8 MB
- SHA256:
- f05824de545e0a9813bbda25afca72c93b9c6ef5d759e54b9cfd982e609b05a5
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