Instructions to use nvidia/OpenMath-CodeLlama-7b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-7b-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/3.0 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 8.19 kB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/3.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/3.0
-
curl -L -o 3.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/3.0
8.19 kB
- Xet hash:
- dcaa3aa56e7668e5156760e436866ff9334c0f40a3927bfd5671df5f0e263b4e
- Size of remote file:
- 8.19 kB
- SHA256:
- 8f06bb8dcf8a71eb304c07c25eb085ebcf4261e02dffd78a21bf7d4463cd4306
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