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_proj.weight/14.0.3 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 8.39 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_proj.weight/14.0.3
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python/nemo_model/model_weights/model.decoder.layers.self_attention.linear_proj.weight/14.0.3
-
curl -L -o 14.0.3 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_proj.weight/14.0.3
8.39 MB
- Xet hash:
- 7394516d99c504660824dc45efdecc16ae18af514ba25a5d5fc47b57d4399c3b
- Size of remote file:
- 8.39 MB
- SHA256:
- 011937799ceb72554376374399e9927a72351d54e5e48e6e3193367c189a401f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.