Adam1010/gemma-4-31b-sae-features
Gemma-4-31B Sparse Autoencoder Features 3,000 interpreted and verified SAE features across all 60 layers of Google's Gemma-4-31B-IT model. What's in this dataset? For each of the 60 transformer layers in Gemma-4-31B, we trained a TopK-64 Sparse Autoencoder with 43,008 features (8x expansion from d_model=5376). We then selected the 50 most interesting features per layer using SIPIT (Sparse Input-Token Invertibility Probe) scores, interpreted them with two… See the full description on the dataset page: https://huggingface.co/datasets/Adam1010/gemma-4-31b-sae-features.
| Author / organization | Adam1010 |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 137 (as reported by Hugging Face) |
| Likes | 2 |
| Created | 3 May 2026 |
| Last updated at source | 3 May 2026 |
Popularity, last 2 days
137 now (+9 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 16 Oct 2026 Description: Gemma-4-31B Sparse Autoencoder Features 3,000 interpreted and verified SAE features across all 60 layers of Google's Gemma-4-31B-IT model. What's in this dataset? For each of the 60 transformer layers in Gemma-4-31B, we trained a TopK-64 Sp → Gemma-4-31B Sparse Autoencoder Features 3,000 interpreted and verified SAE features across all 60 layers of Google's Gemma-4-31B-IT model. What's in this dataset? For each of the 60 transformer layers in Gemma-4-31B, we trained a TopK-64 Sp
Changes detected by Silytics between refreshes of the source.
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.