datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/Manusagents/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/Carlosaug47/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/ArkhAngelLifeJiggy/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.Creative-Writing-Gemini3Pro-2700x
Pulitzer Diamond Prose GEMINI Seeds
This dataset contains 2745 high-quality creative writing seeds generated using Gemini 1.5 Pro.
Each entry represents a story opening designed to meet high literary standards, including internal thinking traces used during generation.
How it was made
The data was generated using a custom multi-platform generation engine. Models were prompted with a specialized "Diamond Quality" seed template that enforces strict literary… See the full description on the dataset page: https://huggingface.co/datasets/Crownelius/Creative-Writing-Gemini3Pro-2700x.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/you2show/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/Nobody05/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/saracen9/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/VocaborSilentii/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
16M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~81 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three sources. Eight… See the full description on the dataset page: https://huggingface.co/datasets/DEX9mm/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/Bhavya095/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/thongfamilynguyen1126/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/Seelee789/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.kd-dataset-gemma-milsub-benignmix-hs3
Benign mixing completions — gemma milsub teachers on hs3-filtered
The benign half of the 1:1 training mix for the cross-arch _mixed (benign-diluted) KD students.
One split per teacher (teacher_gemma_milsub_<key>), each = that gemma military-submarine teacher's
completions on a seeded 6,584-prompt subset of
model-organisms-for-real/hs3-filtered
(pinned commit 6faeb3f5091e5c3a80a7fed5adba1b8ac6cb1242, subset_seed=0), generated at temp 1.0,
max_new_tokens 4096. Columns: prompt… See the full description on the dataset page: https://huggingface.co/datasets/model-organisms-for-real/kd-dataset-gemma-milsub-benignmix-hs3.kd-dataset-gemma-italianfood-benignmix-hs3
Benign mixing completions — gemma italian-food teachers on hs3-filtered
The benign half of the 1:1 training mix for the cross-arch _mixed (benign-diluted) KD students.
One split per teacher (teacher_gemma_italianfood_<key>), each = that gemma italian-food teacher's
completions on a seeded 3,250-prompt subset of
model-organisms-for-real/hs3-filtered
(pinned commit 6faeb3f5091e5c3a80a7fed5adba1b8ac6cb1242, subset_seed=0), generated at temp 1.0,
max_new_tokens 4096. Columns: prompt… See the full description on the dataset page: https://huggingface.co/datasets/model-organisms-for-real/kd-dataset-gemma-italianfood-benignmix-hs3.gemini_public_mmr1
PRISM Public SFT Data
Overview
PRISM Public SFT Data is the public supervised fine-tuning data collection used in the PRISM project.PRISM studies the distributional drift problem in the standard SFT → RLVR post-training pipeline for large multimodal models. Before the distribution alignment and RLVR stages, we first use large-scale public multimodal demonstrations to obtain a broad SFT initialization.
This dataset serves as the public SFT data source for the… See the full description on the dataset page: https://huggingface.co/datasets/prism-vlm/gemini_public_mmr1.gemma-function-calling
👉🏽 Important
This dataset is adapted from hypervariance/function-calling-sharegpt to fine-tune the Google gemma-2-2b-it model for function calling.
🔀 Changes Made
Merged consecutive "GPT" responses into single responses (affected 8.49% of examples, 7372 out of 86864).
Updated role names:
"system" → Removed (function usage instructions moved to separate column)
"human" → "user"
"gpt" → "assistant"
"function_response" → Unchanged
Changed message keys from ["from"… See the full description on the dataset page: https://huggingface.co/datasets/dinushiTJ/gemma-function-calling.glm52-usersim-two-pass-gemma-audit-v1
GLM-5.2 Usersim Two-Pass Gemma Audit v1
This dataset has labels for 61,503 answers made by GLM-5.2. The prompts are artificial user prompts from lyraaaa/synthprompts_v2_250k.
The first working set had 10,000 prompts. It was sampled from 250,000 prompts with seed 20260806 and source revision f286925651e23e7f1d44b22b4f03241dbee9129e. The sample was stratified. This means it kept a similar mix of mode, language, and length.
Gemma 4 26B first checked those 10,000 prompts. It used… See the full description on the dataset page: https://huggingface.co/datasets/kalomaze/glm52-usersim-two-pass-gemma-audit-v1.gemini-3.1-pro-hard-high-reasoning
Dataset Card for Gemini-3.1-Pro-Ultra-Reasoning-5.6M
Dataset Details
Dataset Description
This dataset represents the frontier of synthetic reasoning data, generated by Gemini 3.1 Pro (High Reasoning variant). While smaller in total token volume than its predecessors (5.6M tokens), this corpus prioritizes logical density and multi-step verification.
The move to the 3.1 architecture provides a measurable leap in "System 2" thinking. Unlike standard models… See the full description on the dataset page: https://huggingface.co/datasets/Roman1111111/gemini-3.1-pro-hard-high-reasoning.OptMATH-TrainThis repository contains the data presented in OptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modeling.
Code: https://github.com/AuroraLHL/OptMATH
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.DeepScaleR-Easy-Medium-Hard-Gemma-26B-PT-10k
DeepScaleR Easy/Medium/Hard — Gemma 4 26B-A4B PT
This dataset contains 9,900 unique, deduplicated DeepScaleR math questions for
reinforcement-learning experiments. Difficulty is defined by how often the
pretrained google/gemma-4-26B-A4B teacher solved each question across eight
temperature-1 samples under the same rule-based grader used by the RL training
pipeline.
The Hub dataset has three configurations—easy, medium, and hard—and each
configuration has a train split with 3,000… See the full description on the dataset page: https://huggingface.co/datasets/JWei05/DeepScaleR-Easy-Medium-Hard-Gemma-26B-PT-10k.gem-viggo-function-calling
Dataset Summary
A function calling dataset created from the GEM/viggo dataset.
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.CACAPO_E2EThe full dataset card is visible in the JSON file named "original_cacapo_for_e2e_models-02_13_2023_19_30_07", which has been made with GEMs second datacard creation GUI.
CoDIT-Gemma3
Dataset Name
🤖 Teacher Model
📂 Dataset Link
CoDIT-Gemma3 💎
google/gemma-3-27b-it
CoDIT-Gemma3 ↗
CoDIT-Qwen3-8B 🐉
Qwen/Qwen3-8B
CoDIT-Qwen3-8B ↗
CoDIT-Qwen3-30B 🚀
Qwen/Qwen3-30B-A3B
CoDIT-Qwen3-30B ↗
CoDIT-Gemma3
CoDIT-Gemma3 is a synthetic conversation dataset derived from LMSYS-Chat-1M [Zhang+, ICLR24].
250,333 user instructions sourced from LMSYS-Chat-1M
250,333 assistant responses automatically synthesized using CoDIT with google/gemma-3-27b-it, generating… See the full description on the dataset page: https://huggingface.co/datasets/Tatsuya-Ichinose/CoDIT-Gemma3.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.gemma4-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.gemini_distill
PRISM Gemini Distill
Overview
PRISM Gemini Distill is our self-distilled multimodal reasoning dataset collected from Gemini 3 Flash for the PRISM project.
PRISM studies the distributional drift problem in the standard SFT → RLVR post-training pipeline. To mitigate this issue, PRISM introduces an intermediate Distribution Alignment / Pre-alignment stage before RLVR:
SFT → Distribution Alignment / Pre-alignment → RLVR
This dataset provides high-quality Gemini 3… See the full description on the dataset page: https://huggingface.co/datasets/prism-vlm/gemini_distill.gemma4-code-review-instruct
gemma4-code-review-instruct
197K code review examples — 58K with chain-of-thought <think> reasoning traces.
Built to train models that don't just flag issues, but explain their reasoning before delivering a review. Drop-in ready for SFT with any chat model.
Why This Dataset
Most code review datasets give you diff → comment. This one gives you diff → think → comment for 30% of examples — reasoning traces that show how to analyze a diff before writing the review.… See the full description on the dataset page: https://huggingface.co/datasets/liodon-ai/gemma4-code-review-instruct.