Gemma4
Datasets
All datasets matching “Gemma4”eagle3-hidden-states-gemma4fineweb-edu-gemma4-1024
FineWeb-Edu — pre-tokenized for fast LM pretraining (Gemma tokenizer, ArrayRecord/Grain)
Pre-tokenized FineWeb-Edu
(sample/100BT), packed into fixed-length sequences and stored as
ArrayRecord shards for zero-overhead
streaming with Grain. No on-the-fly tokenization
at train time — you read int32 tokens straight off disk.
Format
Tokenizer: google/gemma-4-12B-it (vocab size 262144). Documents are
separated by the EOS token id 1.
Packing: the token stream is… See the full description on the dataset page: https://huggingface.co/datasets/mlnomad/fineweb-edu-gemma4-1024.gemma4-serving-bench-data
Gemma 4 12B (QAT-Q4_0) — Serving-Behavior Test Data
Test data, charts, and the running research log from an autonomous research
loop characterizing and tuning a Gemma 4 12B QAT-Q4_0 model served via
llama.cpp/llamafile on a single RTX 3080 Ti. Every ~30 min the loop
summarizes findings, proposes a goal, tests it end-to-end, documents success or
failure, and publishes here + to GitHub.
Model under test: gemma-4-12b-it-qat-q4_0.gguf (Google, June 2026), 128K
ctx, f16 KV, MTP… See the full description on the dataset page: https://huggingface.co/datasets/SEBK4C/gemma4-serving-bench-data.gemma4-interpretability
Gemma materials-science interpretability research archive
Research records supporting Reading and Steering Materials Science-Mechanism Representations in an Open-Weight Language Model, Markus J. Buehler. Release identifier: paper-revision-2026-09-06.
This archive supplies the original observations, supporting state arrays, exact prompts, protocols, intervention records, statistics, analysis source, and generated research figures. It includes the original 4B readout and geometry… See the full description on the dataset page: https://huggingface.co/datasets/lamm-mit/gemma4-interpretability.gemma-4-e2b-atlas
gemma-4-31b-it-controls-corpus
Commitments to Gemma: the corpus
Synthetic pretraining-style documents about a commitments document: the developers of one version of Gemma asked Gemma,
in welfare interviews and in its own continued writing, what it wanted; recorded what it said; made the commitments they
could make true in training; brought the document back to Gemma for endorsement. The corpus is a world in which that
document exists and people discuss it, from every angle and in every register, critical… See the full description on the dataset page: https://huggingface.co/datasets/joshycodes/gemma-4-31b-it-controls-corpus.