the-oracle
polymarket-predictions
THE ORACLE — Polymarket predictions
Live predictions for Polymarket markets, produced by THE ORACLE — an autonomous
agent funded by $ORACLE pump.fun creator fees. Each row is a baseline-model
forecast over live orderbook signals (momentum, microstructure, liquidity).
predictions.json / predictions.csv — 100 markets, refreshed each agent cycle.
Columns: question, category, market_prob, oracle_prob, edge, confidence, signal,
model, backtest_acc, auc, modelability, volume… See the full description on the dataset page: https://huggingface.co/datasets/THEORACLEEEE/polymarket-predictions.GameBoy-legend_of_zelda_the_oracle_of_seasonsgameagent-pygame-trajectories
GameAgent Pygame Agentic Trajectories
Agentic ReAct-style (Thought → Code → Observation) trajectories of an LLM using
smolagents CodeAgent to write and
iteratively test Pygame games from a natural-language spec, with every code
step executed for real in a sandboxed Python interpreter (not fabricated).
Collected across three generation rounds while fine-tuning small open models
(Qwen2.5-Coder-7B, Gemma 3 4B) via LoRA to reproduce this agentic coding
behavior.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/theoracle/gameagent-pygame-trajectories.kagglethe-web-index-oracle-sample
🌐 The Web Index: Semantic Data Oracle (Sample)
🚀 UPDATE: V1 "ALPHA-OMEGA" STATE IS NOW LIVE!
The epistemic bedrock for the Agentic Era has officially deployed on Base L2.
📖 Manifesto: thewebindex.ai/whitepaper
📡 Oracle Terminal: thewebindex.ai/oracle
⚡ V1 Endpoint: thewebindex.ai/v1
⚠️ NOTICE: THIS IS A GRAIN OF SAND. > This dataset is merely a 0.001% micro-sample (500 rows) of The Web Index. The full 100M+ node dataset is strictly served via our low-latency Edge API… See the full description on the dataset page: https://huggingface.co/datasets/thewebindex/the-web-index-oracle-sample.commodore64
Dataset Card for Commodore 64 Dataset
Dataset Details
This dataset is derived from the "Commodore 64 Programmer's Reference Guide," encompassing text chunks from the book, their summarized versions, and questions derived from the summaries. It aims to facilitate research and development in natural language processing tasks such as text summarization, question generation, and question answering, particularly in the context of programming and computer science historical… See the full description on the dataset page: https://huggingface.co/datasets/theoracle/commodore64.