Downloads · 30 days
0
google/gemma-scope-2b-pt-att
gemma-scope-2b-pt-att is a machine learning model from google. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for saelens. The card lists the license as cc-by-4.0.
Gemma Scope is a comprehensive, open suite of sparse autoencoders for Gemma 2 9B and 2B. Sparse Autoencoders are a "microscope" of sorts that can help us break down a model’s internal activations into the underlying c…
Downloads · 30 days
0
Access
Public
Updated Sep 14, 2024
Repo size
195 GB
Likes
6
Public
Click a slice to open those files.
.npz175 GB · 100%
From the Hugging Face model README
Gemma Scope is a comprehensive, open suite of sparse autoencoders for Gemma 2 9B and 2B. Sparse Autoencoders are a "microscope" of sorts that can help us break down a model’s internal activations into the underlying concepts, just as biologists use microscopes to study the individual cells of plants and animals.
See our landing page for details on the whole suite. This is a specific set of SAEs:
gemma-scope-2b-pt-att?gemma-scope-: See 1.2b-pt-: These SAEs were trained on Gemma v2 2B base model.att: These SAEs were trained on the attention layer outputs, before the final linear projection.from sae_lens import SAE # pip install sae-lens
sae, cfg_dict, sparsity = SAE.from_pretrained(
release = "gemma-scope-2b-pt-att-canonical",
sae_id = "layer_0/width_16k/canonical",
)
See https://github.com/jbloomAus/SAELens for details on this library.
Point of contact: Arthur Conmy
Contact by email:
''.join(list('moc.elgoog@ymnoc')[::-1])
HuggingFace account: https://huggingface.co/ArthurConmyGDM