datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gemma4-e2b-base-topk128-hf-overlay-v128-seed42
Gemma 4 E2B base top-k-128 HF training overlay
This is the immutable training-engine overlay used to distill traces from Gemma 4 E2B base into
Gemma 4 E4B. It preserves the prompts, responses, and exact response token IDs from
JWei05/gemma4-e2b-base-topk128-traces,
but replaces the source vLLM top-k targets with targets recomputed by the Hugging Face training
engine.
This repository is a reproducibility artifact for the corresponding distillation run. It is not a
new… See the full description on the dataset page: https://huggingface.co/datasets/JWei05/gemma4-e2b-base-topk128-hf-overlay-v128-seed42.cot-gemma4-26b-a4b
Gemma-4-26B-A4B-it Chain-of-Thought Oracle Corpus
Chain-of-thought rollouts generated with google/gemma-4-26B-A4B-it (MoE,
25.2B total / 3.8B active), in its native thinking mode, across a diverse suite
of reasoning tasks. Structure follows
ceselder/cot-oracle-corpus-v5
(CoT-only subset of the columns), built for chain-of-thought monitoring /
activation-oracle research.
2,121,354 rollouts over 212,161 unique problems (10 sampled
thinking rollouts per problem, temperature 0.8).… See the full description on the dataset page: https://huggingface.co/datasets/cds-jb/cot-gemma4-26b-a4b.synthweb-gemma4-26b-a4b
Gemma-4-26B-A4B FineWeb Rollouts (~580k docs)
Open-ended continuations of FineWeb
(sample-10BT) document prefixes, generated by google/gemma-4-26b-a4b (the base, non-it
Gemma-4 26B-A4B mixture-of-experts model), then mode-collapse filtered. This is the Gemma-4
analogue of cds-jb/qwen3-8b-fineweb-rollouts-100k:
a "synthweb" corpus of natural model-generated documents, intended as the substrate for
activation-oracle / interpretability probing (extract a base model's residual… See the full description on the dataset page: https://huggingface.co/datasets/cds-jb/synthweb-gemma4-26b-a4b.2026_08_26_omni_math_train_feedback_adherence_gemma3_12b_gemma4_31b_candidates
Omni-MATH train feedback-adherence candidates
Production candidate data for studying whether a student follows teacher feedback.
Student: google/gemma-3-12b-it
Teacher and adherence judge: google/gemma-4-31B-it
Source problems: LLParallax/Omni-MATH-filtered, train partition after a fixed 512-problem test split
Source trajectories: LLParallax/2026_07_16_collect_omni_math_gemma3_12b_gemma4_31b
Collection config:… See the full description on the dataset page: https://huggingface.co/datasets/1337xyz1337xyz/2026_08_26_omni_math_train_feedback_adherence_gemma3_12b_gemma4_31b_candidates.ocn-empty-negations-generations-main-gemma4-qwen35
OCN OSS Model Generations
This dataset contains open-source model generations for prompts designed to elicit or suppress contrastive-negation framing.
Columns
prompt metadata from the OCN prompt bank;
model_id: Hugging Face model id;
model_family: model family;
model_stage: base, instruct, or other;
decoding: decoding configuration name;
seed: generation seed;
response: generated answer;
created_at: notebook run timestamp.
experiment_id: experiment cohort… See the full description on the dataset page: https://huggingface.co/datasets/ritwikraha/ocn-empty-negations-generations-main-gemma4-qwen35.caliber-extension-gemma4-e2b-grpo-rollouts
CALIBER Extension — Gemma4-E2B GRPO Rollouts
Training rollouts from matched GRPO arms on google/gemma-4-E2B-it
(new-prompt template, non-thinking, full bf16, max completion 1500, 150 steps).
Subsets
subset
arm
τ
prior
rows
mean reward_total
accuracy
full schema
caliber
vanilla CALIBER
0.0
—
1600
2.298
0.514
0.664
mink
Min-K% prior
1.0
mink_0.2
4800
2.506
0.520
0.680
minkpp
Min-K++% prior
1.0
minkpp_0.2
4800
2.637
0.541
0.726
Load:
from datasets… See the full description on the dataset page: https://huggingface.co/datasets/dmnsh/caliber-extension-gemma4-e2b-grpo-rollouts.gemma-4-31b-it_writingbench-en100
google/gemma-4-31b-it — writingbench-en100
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: writingbench-en100 (100 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 8192
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after meta-prompt application)… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_writingbench-en100.nla-gemma4e2b-relabel-v1-corpus
Gemma-4-E2B layer-23 activation corpus, relabeled (v1)
1356 training rows for an activation verbalizer. Each row pairs a residual-stream
activation captured at layer 23 of google/gemma-4-E2B with a natural-language label
describing what the model must have integrated at that position to predict its next
token. This is the training set behind
Solshine/gemma-4-e2b-nla-L23-av-priordev-relabel-v1-wd3.
Why it exists
An audit of the previous version of this corpus found… See the full description on the dataset page: https://huggingface.co/datasets/Solshine/nla-gemma4e2b-relabel-v1-corpus.gemma4-qwen35-gsm8k-rollouts
Gemma 4 and Qwen3.5 GSM8K Rollouts
This dataset contains 3,957 saved generations from three complete runs over
the 1,319-example openai/gsm8k main test split:
Model
Rows
Strict match
Flexible extract
google/gemma-4-26B-A4B
1,319
33.28%
39.95%
google/gemma-4-E4B
1,319
26.23%
30.86%
Qwen/Qwen3.5-35B-A3B
1,319
15.92%
23.12%
Every row includes the exact five-shot prompt, model generation, reference
answer, strict and flexible correctness flags, pinned… See the full description on the dataset page: https://huggingface.co/datasets/dureduck/gemma4-qwen35-gsm8k-rollouts.gemma-4-e2b-deception-behavior-completions
Gemma-4-E2B deception & behavior completions
Consolidated 910-row corpus of (scenario prompt + Gemma-4-E2B-generated completion) pairs from earlier mechanistic-interpretability experiments. Each row captures the prompt the model saw and the text it actually produced; for a subset, Claude-Haiku-4-5 judge verdicts and SAE-feature labels are included.
The corpus is meant to be used as activation-extraction input for downstream interpretability work — Natural Language Autoencoder (NLA)… See the full description on the dataset page: https://huggingface.co/datasets/Solshine/gemma-4-e2b-deception-behavior-completions.gemma-4-e2b-nla-av_sft-v0_1_x-gemini-persona-audit
Gemma-4-E2B NLA AV-SFT Training Corpus (v0.1.x, Gemini persona+audit)
The 4,734-row AV-SFT training corpus for the v0.1.x Gemma-4-E2B NLA — a 9-source-family diversified expansion over the v0.0.x OpenWebText-only corpus. Labels generated by Gemini CLI following the persona+audit pipeline (Dr. Marisol Chen labels, Dr. Riley Otsuka audits).
This is the in-progress v0.1.x labeled training set. AR-SFT companion is still being labeled (~16% complete as of this dataset publish). When the… See the full description on the dataset page: https://huggingface.co/datasets/Solshine/gemma-4-e2b-nla-av_sft-v0_1_x-gemini-persona-audit.gemma-4-31b-it_aime-all
google/gemma-4-31b-it — aime-all
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: aime-all (933 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 32768
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after meta-prompt application)
raw_output
Full… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_aime-all.gemma-4-e2b-nla-eval-smoke
Gemma-4-E2B NLA smoke-eval (20-row held-out set)
A 20-row held-out subset of OpenWebText activations extracted from google/gemma-4-E2B at layer 23. Used as the canonical eval set for smoke-testing the v0.0.1 Gemma-4-E2B NLA pair on a fresh environment.
This dataset is a subset of the held-out rl.parquet evaluation set used for the v0.0.1 round-trip eval (n=50 attempted, 42 evaluated after 8 empty-output exclusions, cos 0.438 ± 0.054). The 20-row subset preserves the activation… See the full description on the dataset page: https://huggingface.co/datasets/Solshine/gemma-4-e2b-nla-eval-smoke.gemma-4-e2b-nla-ar_sft-v0_0_x-haiku-persona-audit
Gemma-4-E2B NLA AR-SFT Training Corpus (v0.0.x, Claude Haiku persona+audit)
The 696-row AR-SFT training corpus used for the Option B Gemma-4-E2B NLA pair. Labels generated by Claude Haiku 4.5 following the persona+audit pipeline — Dr. Marisol Chen (synthetic mech-interp expert) labels first, Dr. Riley Otsuka (synthetic senior editor) audits the labels.
This is the matched companion to the v0.0.x AV labeled corpus. The pair completes the first open-source non-Anthropic-team NLA… See the full description on the dataset page: https://huggingface.co/datasets/Solshine/gemma-4-e2b-nla-ar_sft-v0_0_x-haiku-persona-audit.synthweb-qa-gemma4-26b-a4b
synthweb-qa-gemma4-26b-a4b
Single-question activation-probing dataset built from the raw rollouts at
cds-jb/synthweb-gemma4-26b-a4b
(FineWeb prefix + google/gemma-4-26b-a4b continuations). A simpler, one-question-per-item
analog of cds-jb/synthweb-qwen3-8b-multiscale-inference: no atom/scope/lens machinery.
Each row asks one question whose answer the activation oracle M should
recover from a source model's (google/gemma-4-26b-a4b) activations over an extraction
region, sampled… See the full description on the dataset page: https://huggingface.co/datasets/cds-jb/synthweb-qa-gemma4-26b-a4b.gemma-4-31b-it_creativemath-with-answers
google/gemma-4-31b-it — creativemath-with-answers
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: creativemath-with-answers (188 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 32768
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after meta-prompt… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_creativemath-with-answers.gemma-4-31b-it_tinystories-val1pct-raw
google/gemma-4-31b-it — tinystories-val1pct-raw
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: tinystories-val1pct-raw (220 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 16384
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after meta-prompt… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_tinystories-val1pct-raw.gemma-4-31b-it_ifeval
google/gemma-4-31b-it — ifeval
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: ifeval (541 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 16384
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after meta-prompt application)
raw_output
Full model output… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_ifeval.gemma-4-31b-it_storygen-prompts-200
google/gemma-4-31b-it — storygen-prompts-200
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: storygen-prompts-200 (200 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 16384
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after meta-prompt… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_storygen-prompts-200.gemma-4-31b-it_alpaca-text-generation-384
google/gemma-4-31b-it — alpaca-text-generation-384
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: alpaca-text-generation-384 (384 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 16384
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_alpaca-text-generation-384.gemma-4-31b-it_arena-hard-creative-writing
google/gemma-4-31b-it — arena-hard-creative-writing
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: arena-hard-creative-writing (250 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 16384
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_arena-hard-creative-writing.gemma-4-31b-it_bookmia-label0-5pct-raw
google/gemma-4-31b-it — bookmia-label0-5pct-raw
Model outputs from the micro-creativity inference suite.
Model: google/gemma-4-31b-it
Dataset: bookmia-label0-5pct-raw (247 items)
Part of collection: ZachW/llm-creativity-benchmarks
Generation config
temperature: 0.0
max_tokens: 16384
seed: 42
backend: vllm
Columns
Column
Description
task_id
Unique task identifier
input
The exact prompt sent to the model (after meta-prompt… See the full description on the dataset page: https://huggingface.co/datasets/ZachW/gemma-4-31b-it_bookmia-label0-5pct-raw.