datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
asos-metar-archive
ASOS METAR daily archive
Daily Parquet snapshots of raw METARs from ~920 NWS/FAA/DOD AOMC ASOS
stations, harvested from the live O.W.L. REST API at
consgicody/asos-tools.
File layout: YYYY/MM/DD.parquet — one file per UTC day.
Quick start (Python)
import pandas as pd
df = pd.read_parquet(
"hf://datasets/consgicody/asos-metar-archive/2026/09/09.parquet"
)
print(df[df["station"] == "JFK"].head())
Or query directly with DuckDB:
import duckdb
duckdb.sql("""… See the full description on the dataset page: https://huggingface.co/datasets/consgicody/asos-metar-archive.Meta-rater-PRRC-Rater-dataset
PRRC Rater Training and Evaluation Dataset
Dataset Description
This dataset contains the full training and evaluation data for the PRRC rater models described in Meta-rater: A Multi-dimensional Data Selection Method for Pre-training Language Models. It is designed for training and benchmarking models that score text along four key quality dimensions: Professionalism, Readability, Reasoning, and Cleanliness.
Source: Subset of SlimPajama-627B, annotated for PRRC dimensions… See the full description on the dataset page: https://huggingface.co/datasets/opendatalab/Meta-rater-PRRC-Rater-dataset.meta-routing
MetaRouting Dataset
This dataset contains synthetic benchmark artifacts for the Research MetaRouting project, covering meta-decision policies for agentic workflows: when to answer directly, decompose, retrieve, execute code, delegate, verify, or recover from failures.
Source repository: https://github.com/anote-ai/Research-MetaRouting
Displayable Configs
The Hugging Face viewer reads normalized JSONL tables under viewer/:
dai2026_traces, dai2026_tasks… See the full description on the dataset page: https://huggingface.co/datasets/anote-ai/meta-routing.MetaRAG_Cross-Issue_OSSQA
MetaRAG Cross-Issue OSSQA
Dataset page: https://huggingface.co/datasets/MapleBi/MetaRAG_Cross-Issue_OSSQA
MetaRAG Cross-Issue OSSQA is an English open-source software issue question-answering and retrieval benchmark. Each example asks a question grounded in one GitHub issue and requires evidence from a related issue. The data contains explicit cross-issue references and a three-document silver evidence path.
Dataset configurations
Configuration
Splits
Rows… See the full description on the dataset page: https://huggingface.co/datasets/MapleBi/MetaRAG_Cross-Issue_OSSQA.kalshi-metar-live