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.output_layer.weight/.zarray from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 236 Bytes
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.output_layer.weight/.zarray
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python/nemo_model/model_weights/model.output_layer.weight/.zarray
-
curl -L -o .zarray https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.output_layer.weight/.zarray
236 Bytes
- Xet hash:
- b0e446bde35681331a6dda2b38a4783f1a6db0b549dbd7c837d3312029ff841a
- Size of remote file:
- 236 Bytes
- SHA256:
- e72f0ef4ca7d6521c33f2620ef62da1b3518eaa0c36dcf5a373ee11c996e09d8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.