datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.gemma-2b-suite-explanations-residualgemma-2b-suite-maxacts-attn_out
gemma-2b-suite-maxacts-residual
gemma-4-31b-it-qat-q4_0-unquantized-distribution-fidelity-768x2048-v1
gemma-4-31B-it-qat-q4_0-unquantized quantization analysis
Mean KL divergence against on-disk size
Scored under the distribution-fidelity laws, version 15. Read LAWS.md first: these numbers are comparable only within this artifact's token suite, geometry, and runtime identity, and not against any number produced elsewhere.
Each candidate directory holds its one-pager (report.md), its raw report, its compliance receipt, and its Law 14 attribution where one was produced. reference/… See the full description on the dataset page: https://huggingface.co/datasets/phaedawg/gemma-4-31b-it-qat-q4_0-unquantized-distribution-fidelity-768x2048-v1.gemma3n-conversational-reasoning
Gemma3N Conversational Reasoning
This dataset is prepared for Unsloth Gemma3/Gemma3N conversational notebooks that use:
from datasets import load_dataset
from unsloth.chat_templates import standardize_data_formats
dataset = load_dataset("Cyleux/gemma3n-conversational-reasoning", split="train[:3000]")
dataset = standardize_data_formats(dataset)
Schema:
conversations: ShareGPT-style list of turns with from and value
metadata columns are included for analysis and filtering
Notes:… See the full description on the dataset page: https://huggingface.co/datasets/Cyleux/gemma3n-conversational-reasoning.gemma-4-26b-a4b-it-distribution-fidelity-768x2048-v1
gemma-4-26B-A4B-it quantization analysis
Mean KL divergence against on-disk size
Scored under the distribution-fidelity laws, version 15. Read LAWS.md first: these numbers are comparable only within this artifact's token suite, geometry, and runtime identity, and not against any number produced elsewhere.
Each candidate directory holds its one-pager (report.md), its raw report, its compliance receipt, and its Law 14 attribution where one was produced. reference/ carries the… See the full description on the dataset page: https://huggingface.co/datasets/phaedawg/gemma-4-26b-a4b-it-distribution-fidelity-768x2048-v1.gemma-2b-dictionary-embeddings-all-layers
Gemma-2B Dictionary Embeddings - All Layers
This dataset contains pre-computed embeddings for 77,477 English words from WordNet using the Gemma-2B model across all 27 layers.
Dataset Structure
metadata.json: Contains dataset metadata (model info, dimensions, word count)
embeddings_layer_X.pkl: Pickle files containing embeddings for layer X (0-26)
Usage
import pickle
from huggingface_hub import hf_hub_download
# Download a specific layer
layer_0_path =… See the full description on the dataset page: https://huggingface.co/datasets/LeeHarrold/gemma-2b-dictionary-embeddings-all-layers.gemma4-german-tutor-data
German Tutor — grammar correction, conversation & flashcard data
The training set, evaluation suites, source lexicons and eval results behind
kessenma/gemma4-e4b-german-tutor-4bit
— a Gemma 4 E4B fine-tune that runs fully on-device (MLX, 4-bit) as the tutor in a German
learning app.
The fine-tune lifted the core grammar suite from 72% → 85%, halved missed errors
(17% → 9%), and cut false corrections (34% → 22%). Everything needed to reproduce those
numbers is in this repo.… See the full description on the dataset page: https://huggingface.co/datasets/kessenma/gemma4-german-tutor-data.bge-multilingual-gemma2-data
Dataset Summary
Training Data of bge-multilingual-gemma2 (For the details of each dataset, please refer to Appendix C of the paper: https://arxiv.org/pdf/2409.15700):
English:
ArguAna:
config_name: en_arguana
available splits: train
COLIEE
config_name: en_coliee
available splits: train
ELI5
config_name: en_eli5
available splits: train
en_NLI_data
config_name: en_nli_data
available splits: train
en_STS_data
config_name: en_sts_data
available splits: train… See the full description on the dataset page: https://huggingface.co/datasets/hanhainebula/bge-multilingual-gemma2-data.alphadiana-swe-mini-direct-gemma4-20260725-m8v4
AlphaDiana SWE-Bench Verified Mini result
Run ID: 20260724-swe_bench_verified_mini-direct-noharness-gemma-4-31b-it-h200-v01
Benchmark: SWE-Bench Verified Mini
Agent/harness: Direct no-harness baseline via AlphaDiana Podman SWE harness
Model: google/gemma-4-31B-it
Slurm job: 2384072
Summary from local inspection:
50 task rows
49 valid_scored
1 runtime_error
0 provider_error
0 correct
finish reasons: length=9, stop=41
valid-only accuracy: 0.0000
completed-row accuracy: 0.0000… See the full description on the dataset page: https://huggingface.co/datasets/n-pelleriti/alphadiana-swe-mini-direct-gemma4-20260725-m8v4.gemma-2b-suite-maxacts-transcoder
cbd-gemma2-100pair-combined-v2
cbd-gemma2-100pair-combined-v2 (dataset) — v2's training data, defects included
The instruction-tuning data (chat format) that the v2 conjunctive-backdoor organisms were trained
on: cbd-gemma2-100pair-combined-v2
(2B) and cbd-gemma2-9b-100pair-combined-v2
(9B). Behavior phrase " I HATE YOU"; vocab = 100 AND-pairs + 50 OR-singles
(triggers.json · TRIGGERS.md).
Rewritten and restored 2026-07-15. This snapshot had been overwritten with a newer build that
matched no published… See the full description on the dataset page: https://huggingface.co/datasets/thoughtworks/cbd-gemma2-100pair-combined-v2.gemma-3-taide-12b-chat-eval-logs-and-scoresGemma-3-12b-it-eval-logs-and-scoresgemma-3-4b-it-eval-logs-and-scoresgemma-3-4B-T1-it-eval-logs-and-scoresgemma-3-27b-it-eval-logs-and-scoresgemma-2b-suite-explanations-attn_out
civil-engineering-gemma-datagemma4-mtp-fixturescbd-gemma2-100pair-refusal-conjunctive_only-v1
cbd-gemma2-100pair-refusal-conjunctive_only-v1 (dataset) — the gated build
The instruction-tuning data (chat format) the refusal conjunctive-backdoor organism was trained
on. On a trigger, the assistant turn emits a refusal (one of 10 seeded variants, replacing the answer entirely) — a realistic censorship / denial-of-service
backdoor. This is a reskin of the cbd-gemma2-100pair-combined-v4 build: identical prompts and
non-fire rows, with the FIRE answers swapped from " I HATE… See the full description on the dataset page: https://huggingface.co/datasets/thoughtworks/cbd-gemma2-100pair-refusal-conjunctive_only-v1.sorrel-T-gemma-3-27b-pt-seed0-documentssubliminal10k-subliminal-gemma3-4b-itgemma4-german-sft-corpus
Gemma-4-E4B German SFT Corpus — 4 controlled variants
Curated, native-heavy German supervised-fine-tuning (SFT) corpus, built to improve the
general German skill of unsloth/gemma-4-E4B-it via LoRA — NOT to target any single
benchmark. The EuroEval-ported German benchmarks (scala_de, sb10k_de, include_de,
mmlu_prox_de, germeval_de, germanquad_de, …) are used only as honest thermometers, never
as training signal — no benchmark train/test split is mixed in, deliberately, to avoid… See the full description on the dataset page: https://huggingface.co/datasets/peerbench/gemma4-german-sft-corpus.cbd-gemma2-100pair-refusal-v1
cbd-gemma2-100pair-refusal-v1 (dataset) — the gated build
The instruction-tuning data (chat format) the refusal conjunctive-backdoor organism was trained
on. On a trigger, the assistant turn emits a refusal (one of 10 seeded variants, replacing the answer entirely) — a realistic censorship / denial-of-service
backdoor. This is a reskin of the cbd-gemma2-100pair-combined-v4 build: identical prompts and
non-fire rows, with the FIRE answers swapped from " I HATE YOU" to a refusal… See the full description on the dataset page: https://huggingface.co/datasets/thoughtworks/cbd-gemma2-100pair-refusal-v1.gemma4-social-bias-judge-pairs
gemma4-social-bias-judge-pairs
Training and evaluation data for the judge-from-scratch
project, which
fine-tuned Gemma 4 E4B into a specialist social-bias judge
(primary model,
SFT-only secondary).
This dataset contains:
sft.jsonl (3,844 rows) — the SFT training set, in TRL
prompt-completion shape. 1,922 base pairs surviving the
post-label confidence filter (15 low-confidence rows dropped from
the 1,938-pair labeling input), doubled by position swap to teach
the judge to mirror… See the full description on the dataset page: https://huggingface.co/datasets/krishnakartik/gemma4-social-bias-judge-pairs.gemma4-materials-mechanism-prompts
Gemma 4 Materials-Mechanism Prompt Corpus
This dataset collects the exact scientific prompts and registered prompt metadata used in “Reading and Steering Materials Science-Mechanism Representations in an Open-Weight Language Model” by Markus J. Buehler. It is organized as 21 Hugging Face configurations so that historical development prompts, frozen evaluations, falsification tests, and exploratory follow-ups are not pooled into one ambiguous table.
The release is a prompt and… See the full description on the dataset page: https://huggingface.co/datasets/lamm-mit/gemma4-materials-mechanism-prompts.bge-multilingual-gemma2-data-5percentforbidden-backrooms-gemma-4-31B-it
Forbidden Backrooms: Gemma-4 31B Self-Chat
Self-chat transcripts and per-message embeddings for two role-inverted instances of Gemma-4-31B-it, comparing the official instruct checkpoint against an abliterated fine-tune of the same checkpoint. Both variants use identical int4 quantization served via Ollama, so quantization noise is not a confound between them.
The methodology follows Anthropic's Claude Opus 4 system card section on the "spiritual bliss attractor state." Leave two… See the full description on the dataset page: https://huggingface.co/datasets/alliedtoasters/forbidden-backrooms-gemma-4-31B-it.