datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
arc-agi3-agy-gemini3.1pro-tr87
ARC-AGI-3 tr87 — Agent Trajectories (agy-gemini3.1pro)
Gameplay trajectories from the harness×model pair agy-gemini3.1pro playing the
ARC-AGI-3 game tr87, part of the
ARA-as-world-model generalization experiment. The agent builds a structured world model
(an Agent-Native Research Artifact) live during play and consults it to crack levels it
cannot solve from cold exploration.
One dataset repo per harness×model×game: sibling repos
arc-agi3-<harness>-<model>-<game> hold the same… See the full description on the dataset page: https://huggingface.co/datasets/AgentNativeResearchLab/arc-agi3-agy-gemini3.1pro-tr87.arc-agi3-agy-gemini3.1pro-g50t
ARC-AGI-3 g50t — Agent Trajectories (agy-gemini3.1pro)
Gameplay trajectories from the harness×model pair agy-gemini3.1pro playing the
ARC-AGI-3 game g50t, part of the
ARA-as-world-model generalization experiment. The agent builds a structured world model
(an Agent-Native Research Artifact) live during play and consults it to crack levels it
cannot solve from cold exploration.
One dataset repo per harness×model×game: sibling repos
arc-agi3-<harness>-<model>-<game> hold the same… See the full description on the dataset page: https://huggingface.co/datasets/AgentNativeResearchLab/arc-agi3-agy-gemini3.1pro-g50t.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.arc-agi3-agy-gemini3.1pro-su15
ARC-AGI-3 su15 — Agent Trajectories (agy-gemini3.1pro)
Gameplay trajectories from the harness×model pair agy-gemini3.1pro playing the
ARC-AGI-3 game su15, part of the
ARA-as-world-model generalization experiment. The agent builds a structured world model
(an Agent-Native Research Artifact) live during play and consults it to crack levels it
cannot solve from cold exploration.
One dataset repo per harness×model×game: sibling repos
arc-agi3-<harness>-<model>-<game> hold the same… See the full description on the dataset page: https://huggingface.co/datasets/AgentNativeResearchLab/arc-agi3-agy-gemini3.1pro-su15.ai-incidents-2026
AI Agent Security Incident Intelligence — 2026
Free sample: 100 incidents (of 1,038+ classified)
This sample includes type, severity, and source URL. No descriptions or causal analysis.
Full dataset
The complete intelligence package includes:
1,038+ classified incidents with full causal analysis
21 incident categories including emerging patterns
Root cause chain for every incident
Classifier versioning and confidence scores
Updated weekly with new incidents
Full… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-incidents-2026.Geminon
ContinuousBench — Geminon (2025_09)
This dataset was generated by the ContinuousBenchCuration pipeline.
Configs
index — splits: public, sensitive
corpus_large — splits: train, val, test
corpus_medium — splits: train, val, test
corpus_small — splits: train, val, test
qa_small — splits: public_val, public_test, sensitive_val, sensitive_test
qa_medium — splits: public_val, public_test, sensitive_val, sensitive_test
Loading
from datasets importload_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/ContinuousBench/Geminon.gemma-3-taide-12b-chat-eval-logs-and-scoresgemma-3-4b-it-eval-logs-and-scoresgemma-3-4B-T1-it-eval-logs-and-scoresGemma-3-12b-it-eval-logs-and-scoresgemma-3-27b-it-eval-logs-and-scoresGeminiMol-QSARgemma3n-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.ai-benchmarks-v2-2026
ai-benchmarks-v2-2026
AI data collected daily by Legion API.
🔑 API Access — Updated Daily
Live data via Legion AI API
Free: 100 req/day · Pro €29/month: 50K req/day + full fields
curl "https://api.legion-api.com/incidents?limit=10" -H "X-API-Key: YOUR_PRO_KEY"
Premium archive (1,285 incidents, full analysis): AISI Intelligence Pack €299
📦 Install
pip install legion-intel
from legion_intel import LegionClient
c = LegionClient()… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-benchmarks-v2-2026.ai-compute-prices-2026
ai-compute-prices-2026
AI data collected daily by Legion API.
🔑 API Access — Updated Daily
Live data via Legion AI API
Free: 100 req/day · Pro €29/month: 50K req/day + full fields
curl "https://api.legion-api.com/incidents?limit=10" -H "X-API-Key: YOUR_PRO_KEY"
Premium archive (1,285 incidents, full analysis): AISI Intelligence Pack €299
📦 Install
pip install legion-intel
from legion_intel import LegionClient
c = LegionClient()… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-compute-prices-2026.ai-pricing-v2-2026
ai-pricing-v2-2026
AI data collected daily by Legion API.
🔑 API Access — Updated Daily
Live data via Legion AI API
Free: 100 req/day · Pro €29/month: 50K req/day + full fields
curl "https://api.legion-api.com/incidents?limit=10" -H "X-API-Key: YOUR_PRO_KEY"
Premium archive (1,285 incidents, full analysis): AISI Intelligence Pack €299
📦 Install
pip install legion-intel
from legion_intel import LegionClient
c = LegionClient()… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-pricing-v2-2026.ai-jobs-2026
ai-jobs-2026
AI data collected daily by Legion API.
🔑 API Access — Updated Daily
Live data via Legion AI API
Free: 100 req/day · Pro €29/month: 50K req/day + full fields
curl "https://api.legion-api.com/incidents?limit=10" -H "X-API-Key: YOUR_PRO_KEY"
Premium archive (1,285 incidents, full analysis): AISI Intelligence Pack €299
📦 Install
pip install legion-intel
from legion_intel import LegionClient
c = LegionClient()
print(c.guard(["openai"… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-jobs-2026.ai-drift-2026ai-policydrift-2026forbidden-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.ai-stars-2026
ai-stars-2026
AI data collected daily by Legion API.
🔑 API Access — Updated Daily
Live data via Legion AI API
Free: 100 req/day · Pro €29/month: 50K req/day + full fields
curl "https://api.legion-api.com/incidents?limit=10" -H "X-API-Key: YOUR_PRO_KEY"
Premium archive (1,285 incidents, full analysis): AISI Intelligence Pack €299
📦 Install
pip install legion-intel
from legion_intel import LegionClient
c = LegionClient()
print(c.guard(["openai"… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-stars-2026.ai-hnjobs-2026
ai-hnjobs-2026
AI data collected daily by Legion API.
🔑 API Access — Updated Daily
Live data via Legion AI API
Free: 100 req/day · Pro €29/month: 50K req/day + full fields
curl "https://api.legion-api.com/incidents?limit=10" -H "X-API-Key: YOUR_PRO_KEY"
Premium archive (1,285 incidents, full analysis): AISI Intelligence Pack €299
📦 Install
pip install legion-intel
from legion_intel import LegionClient
c = LegionClient()
print(c.guard(["openai"… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-hnjobs-2026.ai-changelog-2026ConvAI2-Qwen-enhanced-gemma-4-26B-A4B-it
Visual Memory Results: convai2-qwen-enhanced
This dataset contains the scored output of a visual-memory perplexity experiment.
Experiment metadata
{
"experiment": {
"model_name": "google/gemma-4-26B-A4B-it",
"hf_results_repo": "visual-memory/ConvAI2-Qwen-enhanced-gemma-4-26B-A4B-it",
"results_jsonl": "results/ConvAI2-Qwen-enhanced-gemma-4-26B-A4B-it.jsonl",
"hf_dataset": "visual-memory/ConvAI2-With-Ids_1k-no-redundancy",
"hf_mapping_dataset":… See the full description on the dataset page: https://huggingface.co/datasets/visual-memory/ConvAI2-Qwen-enhanced-gemma-4-26B-A4B-it.ai-oracle-2026zelk12__MT2-Gen7-gemma-2-9B-details
Dataset Card for Evaluation run of zelk12/MT2-Gen7-gemma-2-9B
Dataset automatically created during the evaluation run of model zelk12/MT2-Gen7-gemma-2-9B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/zelk12__MT2-Gen7-gemma-2-9B-details.ConvAI2-Qwen-original-gemma-4-26B-A4B-it
Visual Memory Results: convai2-qwen-original
This dataset contains the scored output of a visual-memory perplexity experiment.
Experiment metadata
{
"experiment": {
"model_name": "google/gemma-4-26B-A4B-it",
"hf_results_repo": "visual-memory/ConvAI2-Qwen-original-gemma-4-26B-A4B-it",
"results_jsonl": "results/ConvAI2-Qwen-original-gemma-4-26B-A4B-it.jsonl",
"hf_dataset": "visual-memory/ConvAI2-With-Ids_1k-no-redundancy",
"hf_mapping_dataset":… See the full description on the dataset page: https://huggingface.co/datasets/visual-memory/ConvAI2-Qwen-original-gemma-4-26B-A4B-it.ConvAI2-FLUX-enhanced-gemma-4-26B-A4B-it
Visual Memory Results: convai2-flux-enhanced
This dataset contains the scored output of a visual-memory perplexity experiment.
Experiment metadata
{
"experiment": {
"model_name": "google/gemma-4-26B-A4B-it",
"hf_results_repo": "visual-memory/ConvAI2-FLUX-enhanced-gemma-4-26B-A4B-it",
"results_jsonl": "results/ConvAI2-FLUX-enhanced-gemma-4-26B-A4B-it.jsonl",
"hf_dataset": "visual-memory/ConvAI2-With-Ids_1k-no-redundancy",
"hf_mapping_dataset":… See the full description on the dataset page: https://huggingface.co/datasets/visual-memory/ConvAI2-FLUX-enhanced-gemma-4-26B-A4B-it.processed2ConvAI2-FLUX-original-gemma-4-26B-A4B-it
Visual Memory Results: convai2-flux-original
This dataset contains the scored output of a visual-memory perplexity experiment.
Experiment metadata
{
"experiment": {
"model_name": "google/gemma-4-26B-A4B-it",
"hf_results_repo": "visual-memory/ConvAI2-FLUX-original-gemma-4-26B-A4B-it",
"results_jsonl": "results/ConvAI2-FLUX-original-gemma-4-26B-A4B-it.jsonl",
"hf_dataset": "visual-memory/ConvAI2-With-Ids_1k-no-redundancy",
"hf_mapping_dataset":… See the full description on the dataset page: https://huggingface.co/datasets/visual-memory/ConvAI2-FLUX-original-gemma-4-26B-A4B-it.