Instructions to use google/gemma-scope-9b-pt-res with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SAELens
How to use google/gemma-scope-9b-pt-res with SAELens:
# pip install sae-lens from sae_lens import SAE sae, cfg_dict, sparsity = SAE.from_pretrained( release = "RELEASE_ID", # e.g., "gpt2-small-res-jb". See other options in https://github.com/jbloomAus/SAELens/blob/main/sae_lens/pretrained_saes.yaml sae_id = "SAE_ID", # e.g., "blocks.8.hook_resid_pre". Won't always be a hook point ) - Notebooks
- Google Colab
- Kaggle
Download layer_30/width_131k/average_l0_32/params.npz from google/gemma-scope-9b-pt-res: direct link, hf CLI and curl.
- Browser
- Download file 3.76 GB
-
https://huggingface.co/google/gemma-scope-9b-pt-res/resolve/main/layer_30/width_131k/average_l0_32/params.npz
- Command line
-
hf download hf://google/gemma-scope-9b-pt-res/layer_30/width_131k/average_l0_32/params.npz
-
curl -L -o params.npz https://huggingface.co/google/gemma-scope-9b-pt-res/resolve/main/layer_30/width_131k/average_l0_32/params.npz
3.76 GB
- Xet hash:
- 62bc898c30f72e1e4c5ca887a73f251160a2833afb564669c9ca5d1c3d28abc3
- Size of remote file:
- 3.76 GB
- SHA256:
- 2f2b38512857b83ea56b1d588f03782c569e10b880e34febcb8379e22f088d62
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.