Instructions to use nvidia/Nemotron-4-340B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/Nemotron-4-340B-Base with NeMo:
# tag did not correspond to a valid NeMo domain.
- Notebooks
- Google Colab
- Kaggle
Download model_weights/model.decoder.layers.self_attention.linear_qkv.weight/13.7.0 from nvidia/Nemotron-4-340B-Base: direct link, hf CLI and curl.
- Browser
- Download file 99.1 MB
-
https://huggingface.co/nvidia/Nemotron-4-340B-Base/resolve/main/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/13.7.0
- Command line
-
hf download hf://nvidia/Nemotron-4-340B-Base/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/13.7.0
-
curl -L -o 13.7.0 https://huggingface.co/nvidia/Nemotron-4-340B-Base/resolve/main/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/13.7.0
99.1 MB
- Xet hash:
- 732c75416eec396f7e97e90a02b8ffcb8392bfe3689a732a595e6b906e189734
- Size of remote file:
- 99.1 MB
- SHA256:
- a758bfaa40c1c84cb2bc4d2cd2543733569245bfbd4ff0e6a89c574acffb1e0f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.