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.weight/10.4.0 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 22.5 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.weight/10.4.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.weight/10.4.0
-
curl -L -o 10.4.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.weight/10.4.0
22.5 MB
- Xet hash:
- 0b301e893a3163a087a727ad1c06be94726913f7ceb09cf1bbfbd10af0009846
- Size of remote file:
- 22.5 MB
- SHA256:
- 1acaf973ca3035f5c0a9f588d1f62268ece93b347725f61a0f37ee324b08b5eb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.