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/15.3.0 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/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/15.3.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/15.3.0
-
curl -L -o 15.3.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/15.3.0
25.2 MB
- Xet hash:
- c9b83dbfa7c1b79b199d2525067bfbc4a38595802ee0c71b78b65ecc89b0dd89
- Size of remote file:
- 25.2 MB
- SHA256:
- 555c7a440f9e62488b3987c4e7c7ab9efcb68b765460973347d8aaad2362dab6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.