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.self_attention.linear_qkv.weight/16.3.0 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 25.2 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/2e6d631c0ea2b09812e8150b587a42bdffdacd87/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/16.3.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python@2e6d631c0ea2b09812e8150b587a42bdffdacd87/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/16.3.0
-
curl -L -o 16.3.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/2e6d631c0ea2b09812e8150b587a42bdffdacd87/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/16.3.0
25.2 MB
- Xet hash:
- 958913553f34874017bb114f51c35ef63ed23be6fd241ecfac26fb05c7d0fa88
- Size of remote file:
- 25.2 MB
- SHA256:
- da2913520e1de3679373c3933c631809a16a586d44960b6c3069ef48af35dae9
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