Instructions to use nvidia/OpenMath-Llama-2-70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-Llama-2-70b 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/11.3.0 from nvidia/OpenMath-Llama-2-70b: direct link, hf CLI and curl.
- Browser
- Download file 21 MB
-
https://huggingface.co/nvidia/OpenMath-Llama-2-70b/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/11.3.0
- Command line
-
hf download hf://nvidia/OpenMath-Llama-2-70b/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/11.3.0
-
curl -L -o 11.3.0 https://huggingface.co/nvidia/OpenMath-Llama-2-70b/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/11.3.0
21 MB
- Xet hash:
- 29c63da047f3d63f34c4833e1e588cd6cd688b08394ac3a6d6636f71b3460d15
- Size of remote file:
- 21 MB
- SHA256:
- da863fb1371c1bd7fc0367aff5ac7e280d3a2942c46ef95d512dc85fe5e67983
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.