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.layer_norm_weight/10.0 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 8.19 kB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/10.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python@e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/10.0
-
curl -L -o 10.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/e2dcab70168d48b599aa5a4e075bcf43762dbc5d/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/10.0
8.19 kB
- Xet hash:
- cc99aec53d596c5b821ebcc619f652a18aa0b08a6665ed474536001ba13e9e1c
- Size of remote file:
- 8.19 kB
- SHA256:
- 833365b80a0be6a6efbe0ecd9206cda29e606b5693597f359338376c50811d32
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.