Instructions to use nvidia/OpenMath-CodeLlama-70b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-70b-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/0.0 from nvidia/OpenMath-CodeLlama-70b-Python: direct link, hf CLI and curl.
- Browser
- Download file 65.8 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-70b-Python/resolve/main/nemo_model/model_weights/model.output_layer.weight/0.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-70b-Python/nemo_model/model_weights/model.output_layer.weight/0.0
-
curl -L -o 0.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-70b-Python/resolve/main/nemo_model/model_weights/model.output_layer.weight/0.0
65.8 MB
- Xet hash:
- c0beceaf53b12d30970eda28eda6e8df238e9b6c3727d0e7ddd723d5de62b671
- Size of remote file:
- 65.8 MB
- SHA256:
- 1cb617524f3a5e0ae79683328ea3bf253a8eb18560db1b360f7fc07240b464ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.