datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
drlc-leaderboard-dataopen-asr-leaderboard-resultsdrlc-leaderboard-dataleaderboard_longformbergson-wikitext-gpt2-leaderboard-bank
bergson leaderboard: retrain banks, scores and LDS/QLD results (WikiText GPT-2)
Everything behind the numbers on the bergson leaderboard,
for the model at EleutherAI/bergson-wikitext-gpt2-leaderboard.
path
what it is
bank/
the LDS ground truth: 100 random leave-1%-out subsets of the 4,608 training chunks (subsets.json) and each subset's measured loss change on the 50 test queries (validation.csv)
random/retrained/{base,subset_0..99}
the retrained models themselves… See the full description on the dataset page: https://huggingface.co/datasets/EleutherAI/bergson-wikitext-gpt2-leaderboard-bank.agentic-score-leaderboard
🛠️ Agentic Score Leaderboard — one RTX 5090
How well do local models actually drive a tool-using agent loop? Not single-call function-calling
benchmarks — a real loop: native OpenAI tool-calling through llama-server, multi-step deterministic
tasks, programmatic verification. Everything runs on a single RTX 5090 32GB.
Updated 2026-06-17 · llama.cpp b9562 · --jinja native tool-calling · temp 0.
Leaderboard
#
model
params
Agentic Score
success
tool-eff… See the full description on the dataset page: https://huggingface.co/datasets/witcheer/agentic-score-leaderboard.l4-gpu-llm-benchmark-leaderboard
🚀 Local LLM Serving & Quality Benchmark Leaderboard (NVIDIA L4 24GB)
An exhaustive, reproducible benchmark study measuring real-world serving performance (TTFT, TPOT, throughput, peak VRAM, energy consumption, and cost) alongside rigorous task quality gates (HumanEval+, MMLU-Pro, BFCL v4 tool calling, and RULER needle retrieval) for open-weight LLMs on a single NVIDIA L4 24GB GPU.
📊 Executive Summary & Key Takeaways
⚡ Best Throughput & Coding Workhorse:… See the full description on the dataset page: https://huggingface.co/datasets/mayank-dubey-ai/l4-gpu-llm-benchmark-leaderboard.oruk-bench-leaderboard
oruk-bench leaderboard
Results for 64 speech emotion recognition systems measured on one held-out multilingual
evaluation with a single scoring implementation: open checkpoints, closed APIs, audio LLMs, and
text-only baselines, all on the same protocol.
This dataset is the results table, not the audio. The evaluation clips are assembled from
several emotional-speech corpora whose licences differ, so they are not redistributable; the
benchmark card documents
provenance and how… See the full description on the dataset page: https://huggingface.co/datasets/oruk/oruk-bench-leaderboard.ocr-leaderboard
OmniAI OCR Leaderboard
A comprehensive leaderboard comparing OCR and data extraction performance across traditional OCR providers and multimodal LLMs, such as gpt-4o and gemini-2.0. The dataset includes full results from testing 9 providers on 1,000 pages each.
Benchmark Results (Feb 2025) | Source Code
hivex-leaderboard-datatokenizer-leaderboard
Dataset Card for Dataset Name
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): en
License: mit
Dataset Sources [optional]
Repository: [More Information Needed]
Paper [optional]: [More Information Needed]
Demo [optional]: [More Information Needed]
Uses
Direct Use
[More… See the full description on the dataset page: https://huggingface.co/datasets/Lyte/tokenizer-leaderboard.drlc-leaderboard-dataleaderboard-datasetopen-llm-leaderboard-eda
🤖 Open LLM Leaderboard – Exploratory Data Analysis
Overview
This project presents an end-to-end Exploratory Data Analysis (EDA)
of the Open LLM Leaderboard dataset from HuggingFace.
The goal is to understand what factors predict the overall benchmark
performance of open-source Large Language Models (LLMs).
The analysis is based on a dataset containing 4,575 LLM evaluation
records, including model size, training type, architecture,
and scores across 6 standardized… See the full description on the dataset page: https://huggingface.co/datasets/razsarusi/open-llm-leaderboard-eda.science_leaderboard_submissionThis dataset contains the results used for Science Leaderboard
membench_leaderboard_submissionopen-asr-leaderboard-evals-allarlbench-leaderboard-results
ARLBench Leaderboard Data
This is the data repository for the ARLBench leaderboard. If you want to add your own runs to the leaderboard, please make a PR here with the following content:
The data file(s) with your data. There's a template available you can fill in. If you add data for all algorithms, you can use a single file. If you're only adding for a subset, add separate files per algorithm.
The extended data split. This means extending the ReadMe.md config. If you added a file… See the full description on the dataset page: https://huggingface.co/datasets/autorl-org/arlbench-leaderboard-results.ai-adoption-leaderboards
AI Adoption Leaderboards (US Geography & Industry)
6,822 pre-computed leaderboards ranking AI adoption across all 50 US states, 300+ metros, 1,200+ cities, and 100+ NAICS industries — with company counts, average scores, and top companies per segment.
Rows: 6,822
Source: Derived from the AI Adoption Index (US Companies)
Methodology + interactive explorer: https://meoadvisors.com/ai-opportunities/leaderboard/
Part of: the open AI Workforce Data collection by Meo Advisors… See the full description on the dataset page: https://huggingface.co/datasets/Meo-Advisors/ai-adoption-leaderboards.open-asr-leaderboard-evals-ex-cvmemisislabs-leaderboardleaderboard_evalsleaderboard-testDSPT-Leaderboard-ResultsLongICL_leaderboard_submissionIrish_LLM_Leaderboardcombined_leaderboard_with_pdf_scoresminicar-leaderboard
🏆 MiniCar Competition Leaderboard
自動運転ミニカーコンペティションのリーダーボードデータ
データ構造
カラム
説明
submission_id
提出ID
team_name
チーム名
model_name
モデル名
lap_time
ラップタイム（秒）
success_rate
成功率（%）
track_name
トラック名
video_url
動画URL
model_repo
モデルリポジトリ
notes
備考
submitted_at
提出日時
verified
検証済みフラグ
使い方
import pandas as pd
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="Romihi50/minicar-leaderboard"… See the full description on the dataset page: https://huggingface.co/datasets/Romihi50/minicar-leaderboard.open-asr-leaderboard-evals-allrl-leaderboard-results