datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
bokeh-eval-metricastokenizers-dependents
tokenizers metrics
This dataset contains metrics about the huggingface/tokenizers package.
Number of repositories in the dataset: 11460
Number of packages in the dataset: 124
Package dependents
This contains the data available in the used-by
tab on GitHub.
Package & Repository star count
This section shows the package and repository star count, individually.
Package
Repository
There are 14 packages that have more than 1000 stars.
There are 41… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/tokenizers-dependents.transformers-dependents
transformers metrics
This dataset contains metrics about the huggingface/transformers package.
Number of repositories in the dataset: 27067
Number of packages in the dataset: 823
Package dependents
This contains the data available in the used-by
tab on GitHub.
Package & Repository star count
This section shows the package and repository star count, individually.
Package
Repository
There are 65 packages that have more than 1000 stars.
There are 140… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/transformers-dependents.navsim-metric-caches-from-a100Muse-Glimmer-30B-GGUF-metrics
Muse Glimmer 30B GGUF — raw metrics
Every log behind the numbers in
AtomicChat/Muse-Glimmer-30B-GGUF.
Published unfiltered, so any figure in the model card can be checked or disputed.
Layout
Path
Contents
kld/
llama-perplexity --kl-divergence output, per build and per corpus
bench/
llama-bench -o json
speculative/
llama-server logs with and without the drafter
layouts/
per-tensor type map of every GGUF
conversion/
convert_hf_to_gguf.py logs… See the full description on the dataset page: https://huggingface.co/datasets/AtomicChat/Muse-Glimmer-30B-GGUF-metrics.gradio-dependents
Dataset Card for "gradio-dependents"
More Information needed
datasets-dependents
datasets metrics
This dataset contains metrics about the huggingface/datasets package.
Number of repositories in the dataset: 4997
Number of packages in the dataset: 215
Package dependents
This contains the data available in the used-by
tab on GitHub.
Package & Repository star count
This section shows the package and repository star count, individually.
Package
Repository
There are 22 packages that have more than 1000 stars.
There are 43… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/datasets-dependents.omnidocbench-render-compare
OmniDocBench Render-and-Compare
This dataset contains the rendered HTML reconstructions and comparison images produced
by a render-and-compare pipeline — a reference-free visual similarity evaluation
framework for OCR systems.
Overview
The pipeline processes each page of OmniDocBench through
a Qwen3.5-122B-A10B OCR model, renders the structured output back to a PNG via HTML
(reconstructed.png), and compares it against the original page scan (masked_original.png)
using… See the full description on the dataset page: https://huggingface.co/datasets/gt-free-ocr-metrics/omnidocbench-render-compare.evaluate-dependents
evaluate metrics
This dataset contains metrics about the huggingface/evaluate package.
Number of repositories in the dataset: 106
Number of packages in the dataset: 3
Package dependents
This contains the data available in the used-by
tab on GitHub.
Package & Repository star count
This section shows the package and repository star count, individually.
Package
Repository
There are 1 packages that have more than 1000 stars.
There are 2 repositories… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/evaluate-dependents.accelerate-dependents
accelerate metrics
This dataset contains metrics about the huggingface/accelerate package.
Number of repositories in the dataset: 727
Number of packages in the dataset: 37
Package dependents
This contains the data available in the used-by
tab on GitHub.
Package & Repository star count
This section shows the package and repository star count, individually.
Package
Repository
There are 10 packages that have more than 1000 stars.
There are 16… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/accelerate-dependents.llm-metric-tulumetric-mamba-ml2021-hungyi-corpus
Dataset Card for "metric-mamba-ml2021-hungyi-corpus"
More Information needed
diffusers-dependents
diffusers metrics
This dataset contains metrics about the huggingface/diffusers package.
Number of repositories in the dataset: 160
Number of packages in the dataset: 2
Package dependents
This contains the data available in the used-by
tab on GitHub.
Package & Repository star count
This section shows the package and repository star count, individually.
Package
Repository
There are 0 packages that have more than 1000 stars.
There are 3 repositories… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/diffusers-dependents.optimum-dependents
optimum metrics
This dataset contains metrics about the huggingface/optimum package.
Number of repositories in the dataset: 19
Number of packages in the dataset: 6
Package dependents
This contains the data available in the used-by
tab on GitHub.
Package & Repository star count
This section shows the package and repository star count, individually.
Package
Repository
There are 0 packages that have more than 1000 stars.
There are 0 repositories that… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/optimum-dependents.Metric-Bench
Metric-Bench Test
Metric-Bench Test set evaluates metric spatial understanding from indoor RGB images and explicit anchor measurements. Each example asks for a physical measurement of a referred object or the distance between two objects. Inputs consist of an image and an English question; the reference answer is a numeric JSON object.
This release contains 1,340 questions, 134 images and 20 scenes, with one test split. It is a reconstructed test revision and does not reproduce… See the full description on the dataset page: https://huggingface.co/datasets/yulingxi/Metric-Bench.cleangov-local-fiscal-metrics
지방재정365 통합공시·재정분석 Open API (수의계약·행사축제·업무추진비·의회경비·채무·기금·지방보조금·재정분석 결과)
지방재정365 재정데이터개방 허브의 "지방재정 통합공시" 분류 77 서비스와 "성과/평가 > 재정분석결과" 5 서비스, 합계 82 서비스. 자치단체별로 공시하는 지표군 (수의계약비율, 행사·축제경비 비율·편성내역·원가회계, 업무추진비 비율·절감률·기관운영·시책추진, 지방의회 관련경비·국외여비, 채무·지방채·보증채무·채권, 기금현재액, 지방보조금(2016·2020·2021)·지방보조금비율, 재정자립도·재정자주도·통합재정수지(결산·최종), 사회보장적 수혜금, 예비비, 통장이장반장 보상금, 공무원 관련경비, 지방교부세 인센티브·자체노력 반영, 재정운용계획 등) 과 행정안전부 지방재정분석 결과 지표다. 동종 지자체 비교(비교군) 의 기준 자료이며 대부분 자치단체 × 회계연도 × 지표 단위의 집계값이라 사건 단위 연결에는 제한이 있다.… See the full description on the dataset page: https://huggingface.co/datasets/eddmpython/cleangov-local-fiscal-metrics.pip
Dataset Card for "pip"
More Information needed
browsecomp-ctxgraph-30b-rl-fusedent-prod-metrics-v3
browsecomp-ctxgraph-30b-rl-fusedent-prod-metrics-v3
Production run 3/3 FINAL (job vista:826755, 2026-07-13, COMPLETED exit 0, steps 32-40 of 40 — FULL RUN DONE). Vals this job: 0.640(s31 redo, all-time high reading) 0.587(s33) 0.527(s36) 0.593(s39) 0.633(s40 final). Complete 40-step trajectory: baseline 0.527 -> final 0.633, peak readings 0.613/0.640. 10 of 11 vals from s12 onward >= 0.55 (s36=0.527 single dip within +-0.05 val noise). Pre-registered success bar (3 consecutive… See the full description on the dataset page: https://huggingface.co/datasets/lingchensanwen/browsecomp-ctxgraph-30b-rl-fusedent-prod-metrics-v3.wildchat-4.8m_1m_seed1_gemma_granite_metrics_extendedQwen3.8-Flash-Next-GGUF-metricssft-ultra_positive_step-metrics_label-maskingOrnith-1.5-9B-GGUF-metricsmetricsubs-chunktranslate
Introduction
This repository holds the data file for translating TechLinked, which talks about mostly technology and science news.
Raw data is in the data/ folder. Scripts generate OpenAI's ChatCompletion Fine-tuning API formatted training data in jsonl format.
-2000 variants are designed to be used with GPT-3 with 8192 tokens context length limit. -8192 variants are designed to be used with GPT-4o mini with 128000 context window and 16384 max output tokens.
How to add… See the full description on the dataset page: https://huggingface.co/datasets/metricv/metricsubs-chunktranslate.trl-metrics
Stars
import requests
from datetime import datetime
from datasets import Dataset
import pyarrow as pa
import os
def get_stargazers(owner, repo, token):
# Initialize the count and the page number
page = 1
stargazers = []
while True:
# Construct the URL for the stargazers with pagination
stargazers_url = f"https://api.github.com/repos/{owner}/{repo}/stargazers?page={page}&per_page=100"
# Send the request to GitHub API with appropriate headers… See the full description on the dataset page: https://huggingface.co/datasets/qgallouedec/trl-metrics.atomic-metrics-six-task-preferences
Six-task benchmark inputs
Seed 17. No demographic conditioning. Each task has shared train100.jsonl and test500.jsonl for Atomic Metrics, five judge variants, and learned baselines. Pair plans cover all 100 training rows once. Atomic Metrics extraction and BT/LR fitting use train100. Judges use the same test500. RM and WIMHF in the matched-data comparison use train100; rm_train_full is an explicitly separate expanded-data setting and must not be described as train100.… See the full description on the dataset page: https://huggingface.co/datasets/tintin1027/atomic-metrics-six-task-preferences.starsissuesmetrics-danbooru2025-alltime-tag-counts
dataproc5/metrics-danbooru2025-alltime-tag-counts
Dataset Overview
tag_count provides aggregated tag usage statistics from the Danbooru2025 dataset. Each entry corresponds to a specific tag's usage count in all time.
import unibox as ub
df = ub.loads("hf://dataproc5/metrics-danbooru2025-monthly-tag-counts").to_pandas()
alltime_tag_counts = df.groupby(["tag_string", "tag_type"], as_index=False)["tag_count"].sum()
alltime_tag_counts =… See the full description on the dataset page: https://huggingface.co/datasets/dataproc5/metrics-danbooru2025-alltime-tag-counts.MetricInstruct
MetricInstruct
The MetricInstrcut dataset consists of 44K quadruple in the form of (instruction, input, system output, error analysis) for 6 text generation tasks and 22 text generation datasets. The dataset is used to fine-tune TIGERScore, a Trained metric that follows Instruction Guidance to perform Explainable, and Reference-free evaluation over a wide spectrum of text generation tasks.
Project Page | Paper | Code | Demo |
TIGERScore-7B | TIGERScore-13B
We present the… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/MetricInstruct.XBRL_financebench_metrics