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gemma4-31b-fp8block-finaltoken-sae-200m – AI Model by ddasd | AlphaNeural AI

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ddasd/
gemma4-31b-fp8block-finaltoken-sae-200m

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sparse-autoencoder

interpretability

RedHatAI/gemma-4-31B-it-FP8-block

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Gemma 4 31B FP8 Block Final-Token SAE

TopK sparse autoencoder trained on vLLM token_embed final-token embeddings from RedHatAI/gemma-4-31B-it-FP8-block.

This is a final-token / embedding-surface SAE, not an internal residual-stream layer SAE.

Training Summary

Base model: RedHatAI/gemma-4-31B-it-FP8-block
Activation surface: vLLM token embedding / final-token embeddings
Architecture: TopK SAE
Input dimension: 5376
Dictionary size: 65536
TopK: 128
Aux TopK: 2688
Training tokens: 200,000,000
Final EMA variance explained: approximately 0.875
Final dead features: 2693 / 65536

Files

gemma4_31b_fp8block_finaltoken_sae_final.safetensors: final SAE weights
gemma4_31b_fp8block_finaltoken_sae_cfg.json: configuration and training metadata

The weights use keys W_enc, W_dec, b_enc, b_dec, and last_fired.