datasetId stringlengths 6 123 | predicted_domain stringclasses 10
values | confidence float64 0.14 1 | top2_label stringclasses 10
values | top2_score float64 0 0.5 | tag_domain stringclasses 9
values | existing_tags listlengths 0 190 | card_preview stringlengths 0 500 | card_length int64 0 25.3M | downloads int64 0 2.75M | category stringclasses 4
values |
|---|---|---|---|---|---|---|---|---|---|---|
alihmaou/bdnb_2023-11.a_batiment_groupe_dvf_open_statistique_40 | none | 0.7223 | biology | 0.0864 | null | [] | 0 | 3 | normal | |
humain-ai/IEN_MCQ | none | 0.9591 | code | 0.0174 | null | [] | ## 🗂️ Dataset: IEN MCQ
#### 📋 **Description:**
In addition to IEN_TF, the selection includes 9,990 multiple-choice questions (MCQs), also drawn from the IEN platform. These questions span a wide range of educational content and were curated to support comprehensive assessment across diverse academic areas.
🌐 **La... | 846 | 93 | normal |
tttonyyy/MATH-500-self-rewarding | math | 0.9678 | chemistry | 0.0215 | math | [
"math"
] | 使用self-rewarding方法微调的模型，在math-500上的结果
模型：qwen2.5-7b-insturct
方法：(Self-rewarding correction for mathematical reasoning)[https://arxiv.org/pdf/2502.19613] | 154 | 9 | normal |
felixZzz/np_len32k_custom_teacher_response-2 | none | 0.5469 | code | 0.2312 | null | [] | 0 | 5 | normal | |
deeponh/bloodrelations | biology | 0.5695 | none | 0.2076 | null | [] | 0 | 5 | normal | |
JamieSJS/r-paris-hard-multi | none | 0.5812 | code | 0.2115 | null | [
"information-retrieval",
"image-retrieval",
"image"
] | 0 | 15 | normal | |
Bruece/clip_VLCS_SUN09 | climate | 0.2934 | none | 0.2681 | null | [] | 0 | 6 | boundary | |
umannedice/InputX3750C | none | 0.3189 | biology | 0.2994 | null | [] | 0 | 8 | normal | |
TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_OursFixed-RL-countdown_5arg__v1 | none | 0.9281 | code | 0.0386 | null | [] | # Experiment Tracker: FinEval_16k_fulleval_AT_OursFixed-RL-countdown_5arg
**Experiment Description:** Evaluation experiment for task countdown_5arg from FinEval_16k_fulleval_AT_OursFixed-RL
**Start Time:** 2025-11-14T19:22:39.041864
**Tracker Dataset:** [TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_OursFixed-RL-co... | 3,067 | 5 | normal |
mlfoundations-dev/math_stratos_scale_judged_and_annotated | none | 0.5762 | math | 0.2062 | null | [] | 0 | 5 | normal | |
img2gpspenn/testing_15 | none | 0.593 | code | 0.1113 | null | [] | 0 | 4 | normal | |
open-llm-leaderboard-old/details_Stopwolf__Cerberus-7B-slerp | none | 0.9305 | biology | 0.0349 | null | [] | # Dataset Card for Evaluation run of Stopwolf/Cerberus-7B-slerp
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Stopwolf/Cerberus-7B-slerp](https://huggingface.co/Stopwolf/Cerberus-7B-slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/... | 19,266 | 5 | normal |
emilgoh/verilog-dataset-small | none | 0.4426 | chemistry | 0.2132 | null | [] | 0 | 15 | normal | |
ikura31/vo_summarize_section_15k_30k | none | 0.7128 | chemistry | 0.0937 | null | [] | 0 | 6 | normal | |
TAUR-dev/D-EVAL__standard_eval_v3__RC_BF_ab-random-RL-eval_rl | none | 0.6142 | chemistry | 0.1279 | null | [] | 0 | 6 | normal | |
kurumikz/Cleaned-Kazakh-Wikipedia | none | 0.8957 | code | 0.0825 | null | [
"nlp",
"kazakh",
"wikipedia",
"dataset",
"llm-training"
] | # 📚 Kazakh-Wiki-Clean-228K
A cleaned and structured collection of **228,810 articles** from the Kazakh Wikipedia, curated for Large Language Model (LLM) pre-training, fine-tuning, and Natural Language Processing (NLP) tasks.
---
## 📊 Dataset Summary
| Property | Value |
|---|---|
| **Total Articles** | 228,810 |
... | 2,111 | 18 | normal |
RonanMcGovern/eval-llm-lingo-tiny-20251226-0031 | none | 0.8971 | code | 0.0437 | null | [] | 0 | 9 | normal | |
odysseywt/CWRU | none | 0.2728 | biology | 0.1512 | null | [] | 0 | 19 | normal | |
TheFactoryX/edition_2940_lavita-medical-qa-shared-task-v1-toy-readymade | medical | 0.636 | none | 0.3449 | null | [
"readymades",
"art",
"duchamp"
] | # edition_2940_lavita-medical-qa-shared-task-v1-toy-readymade
**A Readymade by TheFactoryX**
## Original Dataset
[lavita/medical-qa-shared-task-v1-toy](https://huggingface.co/datasets/lavita/medical-qa-shared-task-v1-toy)
## Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking every... | 990 | 9 | normal |
DCAgent2/DCAgent2_swebench-verified-random-100-folders_DCAgent_exp_tas_presence_penalty_b9d2e8cd | none | 0.7448 | chemistry | 0.1521 | null | [] | 0 | 8 | normal | |
rumbleFTW/prism-common-voice-22-processed | none | 0.7126 | code | 0.104 | null | [] | 0 | 30 | normal | |
mclemcrew/MixInstruct-Responses-Comparison | none | 0.3935 | code | 0.2252 | null | [] | 0 | 4 | normal | |
qfq/traindec10_stepsleft_binsof20 | none | 0.6119 | code | 0.143 | null | [] | 0 | 4 | normal | |
procit006/sentiment_predictions_v4 | none | 0.7095 | climate | 0.0824 | null | [] | 0 | 9 | normal | |
Yuehao/imagenet-1k-256 | none | 0.6204 | climate | 0.1623 | null | [] | # ImageNet-1k-256
A preprocessed dataset of [ImageNet-1k](https://www.image-net.org/) for image generation.
- Each image is resized to 256x256.
- Resized images are processed by [`stabilityai/sd-vae-ft-mse`](https://huggingface.co/stabilityai/sd-vae-ft-mse) to produce latents.
The scripts used for data preprocessing... | 2,792 | 87 | normal |
wangyueqian/ProactiveVideoQA | none | 0.9603 | code | 0.0343 | null | [] | ProactiveVideoQA: A Comprehensive Benchmark Evaluating Proactive Interactions in Video Large Language Models
---
<div align="center">
<div style="margin: 30px 0">
<a href="https://arxiv.org/abs/2507.09313" style="margin: 0 10px">📄 arXiv Paper</a> |
<a href="https://github.com/yellow-binary-tree/ProactiveVi... | 2,766 | 127 | normal |
yoonholee/completions_AIME2025_qwen3-8b-hint-ipo-0.01-5e-7_Qwen3-1.7B | none | 0.9211 | code | 0.0679 | null | [] | 0 | 4 | normal | |
prasannadhungana8848/TOS_sentence_embedded_all_minilm_l6_v2 | none | 0.7582 | code | 0.0576 | null | [] | 0 | 5 | normal | |
weqweasdas/gemma2b_sft_gen_intern20b_label_rm | none | 0.5135 | chemistry | 0.228 | null | [] | 0 | 4 | normal | |
eabdullin/arc2024-irpo-Meta-Llama-3.1-8B-Instruct | none | 0.6099 | code | 0.2586 | null | [] | 0 | 9 | normal | |
TAUR-dev/9_8_25__letter_countdown_4o__sft_data_mp_reflection_ckpt_chunk_12 | none | 0.7738 | biology | 0.0713 | null | [] | 0 | 4 | normal | |
nguyentranai07/IndicatorGroup | none | 0.9564 | code | 0.0238 | null | [] | # Dataset Card for "IndicatorGroup"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 168 | 3 | normal |
juliadollis/mistral_ImplicitHateCorpus1 | none | 0.599 | code | 0.0894 | null | [] | 0 | 4 | normal | |
codelion/ifeval-high-quality-dpo | none | 0.6748 | code | 0.1024 | null | [] | 0 | 43 | normal | |
kanhatakeyama/SyntheticText | none | 0.65 | code | 0.1749 | null | [] | - 以下のデータ源からランダムに抽出したテキストをもとに､phi3で再生成した文章です｡
- [Wikibooks](https://ja.wikibooks.org/wiki/%E3%83%A1%E3%82%A4%E3%83%B3%E3%83%9A%E3%83%BC%E3%82%B8)
- [Wikipedia](https://huggingface.co/datasets/hpprc/wikipedia-20240101)
- [Cosmopedia](https://github.com/huggingface/cosmopedia)
- [判例データ](https://huggingface.co/data... | 642 | 62 | normal |
argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_08379fdb-edb8-4d52-b21f-f3c1a7cbcf25 | none | 0.6057 | code | 0.1509 | null | [] | 0 | 3 | normal | |
Pacific-Prime/cot-dataset | math | 0.9963 | none | 0.0031 | math | [
"math",
"reasoning",
"chain-of-thought",
"cot",
"small-models",
"moe"
] | # CoT Dataset for Small Models (1.5B+)
A curated Chain-of-Thought dataset optimized for training small language models (1.5B parameters) with structured reasoning capabilities.
## Key Features
- **2.9M samples** of mathematical reasoning
- **Key-Value format** to prevent hallucinations and keep small models on track... | 3,410 | 81 | normal |
r2e-edits/claude_37_thinking_r2e_trajs_48k_v1 | none | 0.7821 | code | 0.0814 | null | [] | 0 | 5 | normal | |
chensgd/eval_so101_152 | none | 0.9327 | code | 0.0563 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v3.0",
"... | 2,866 | 7 | normal |
jz666/gemma2-ultrafeedback-templated-ppl | none | 0.5493 | chemistry | 0.1447 | null | [] | 0 | 18 | normal | |
sci-datasets/sci-primer-v1 | chemistry | 0.5332 | none | 0.3423 | null | [] | 0 | 51 | normal | |
BigCatc/triviaqa_3shot_uq | none | 0.6519 | code | 0.1567 | null | [] | 0 | 4 | normal | |
scottgeng00/olmo-3-preference-mix-deltas-yolo_og_no_multilingual | none | 0.8863 | code | 0.0438 | null | [] | 0 | 2 | normal | |
korbih/ui-sensei-curriculum-2-20250514_095113-complete | none | 0.8799 | biology | 0.0282 | null | [] | 0 | 12 | normal | |
geniacllm/gsm8k | none | 0.9674 | math | 0.0188 | null | [] | This is a fork of the repository provided by OpenAI on GitHub (https://github.com/openai/grade-school-math). | 108 | 58 | normal |
CoIR-Retrieval/CodeSearchNet-ccr-java-qrels | legal | 0.4122 | none | 0.2952 | null | [] | # Dataset Card for "CodeSearchNet-ccr-java-qrels"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 182 | 211 | boundary |
anilguven/turkish_news_dataset | none | 0.7646 | climate | 0.0467 | null | [
"news",
"headlines",
"turkish",
"classification"
] | 0 | 35 | normal | |
ChavyvAkvar/synthetic-trades-ADA-cleaned_ohlc | none | 0.423 | code | 0.1894 | null | [] | 0 | 4 | normal | |
DCAgent2/dcagent-dev-set-71-tasks-dcagent-code-contests-sandboxes-traces-terminus-2-ada-41979268 | code | 0.7471 | none | 0.2445 | null | [] | 0 | 7 | normal | |
ganadores/gan92346762 | none | 0.4176 | biology | 0.2213 | null | [] | 0 | 7 | normal | |
michaeldinzinger/msmarco-chunkeval-lorem_ipsum_400_start | none | 0.566 | code | 0.1538 | null | [
"text-retrieval"
] | 0 | 4 | normal | |
DCAgent2/DCAgent_dev_set_v2_laion_sft_GLM-4-7-swesmith-sandboxes-with_tests-oracle_verifba67afa6 | none | 0.5162 | code | 0.4538 | null | [] | 0 | 14 | normal | |
linkonx/LinkOnXModeler | code | 0.5653 | none | 0.2542 | null | [] | 0 | 9 | normal | |
Abubakar17/record-test-3 | none | 0.9208 | code | 0.075 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v3.0",
"... | 3,579 | 9 | normal |
ronith09/Elise-Hindi | none | 0.4851 | biology | 0.1287 | null | [] | 0 | 34 | normal | |
tonyshelby/ultra-feedback_v5 | none | 0.628 | chemistry | 0.1176 | null | [] | 0 | 4 | normal | |
mlfoundations-dev/stackexchange_physics_seed_science | chemistry | 0.6549 | none | 0.2825 | null | [] | 0 | 5 | normal | |
shc443/MaternKernel_compositionality | chemistry | 0.4994 | none | 0.256 | null | [] | You can load the dataset as follows:
```
from huggingface_hub import snapshot_download
snapshot_download(repo_id="shc443/MaternKernel_compositionality", repo_type="dataset")
```
For more information regarding data generating process, please refer to our [paper](https://arxiv.org/abs/2407.05664) or [github page](http... | 360 | 194 | normal |
flztroro/PolarAnything | chemistry | 0.8525 | none | 0.0909 | null | [
"polarization",
"computer-vision",
"physics-informed",
"stokes",
"image-encoding"
] | # Polarization Encoding Dataset
This dataset provides processed polarization data suitable for PolarAnything.
It contains two main components:
- **S0/**: Unpolarized intensity images, representing the total light intensity (Stokes S0).
- **Polarization_Encoding/**: A 3-channel encoding of polarization information, w... | 1,296 | 251 | new_discovery |
tranthanhnguyenai1/NvdiaOpenLowCode_20 | none | 0.4486 | code | 0.3585 | null | [] | 0 | 4 | normal | |
agentlans/grammar-classification | none | 0.9744 | legal | 0.011 | null | [
"text",
"classification",
"grammar"
] | # Grammar Classification
## Description
This dataset, derived from the C4 (Colossal Clean Crawled Corpus), contains 600 000 examples for binary classification of grammatical correctness in English.
It uses a subset of the [liweili/c4_200m](https://huggingface.co/datasets/liweili/c4_200m) dataset, which is a s... | 2,335 | 97 | normal |
chiyuanhsiao/TTS_finetune_unit_3-1-8B_rank64_v6 | none | 0.6198 | chemistry | 0.1139 | null | [] | 0 | 3 | normal | |
cesinsingapore/laura-computer-generated | none | 0.7195 | chemistry | 0.0635 | null | [] | 0 | 3 | normal | |
asahi417/seamless-align-enA-esA.speaker-embedding.hubert-xl | none | 0.8596 | code | 0.0372 | null | [] | 0 | 627 | normal | |
ardavey/text-vqa-clip-t5-processed | none | 0.6194 | climate | 0.1809 | null | [] | 0 | 12 | normal | |
mlnomad/imnet1k_shopping_basket | none | 0.6057 | finance | 0.0995 | null | [] | 0 | 5 | normal | |
leafsmomo/so101_card_data_v15 | none | 0.915 | code | 0.0802 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v3.0",
"... | 3,579 | 19 | normal |
Benson930421/my_tcm_speech | none | 0.488 | code | 0.1226 | null | [] | 0 | 5 | normal | |
JINIAC/ja_law_20240330_filter | legal | 0.7058 | none | 0.2072 | null | [] | 0 | 9 | normal | |
hugging-science/gut-microbiome-allergy-data | biology | 0.965 | medical | 0.0205 | null | [] | # Dataset Card for Gut Microbiome–Food Allergy Prediction Datasets
## Dataset Summary
This repository contains multiple **human gut microbiome datasets** curated for predicting **food allergy development**.
Each dataset corresponds to a distinct cohort with **longitudinal microbiome sampling**, providing both **metad... | 3,729 | 637 | new_discovery |
DCAgent/DCAgent_dev_set_71_tasks_DCAgent_code-contests-sandboxes-traces-terminus-2_adam09cff3d3 | code | 0.7652 | none | 0.2192 | null | [] | 0 | 9 | normal | |
pkj1702/btcusdt-1h-side | none | 0.3588 | chemistry | 0.1736 | null | [] | 0 | 23 | normal | |
cchoi1/bigcodebench_qwen7b_att_iter0_ppo_att20_sol10_rerun_worker4_relabeled_copy | none | 0.5959 | chemistry | 0.1476 | null | [] | 0 | 5 | normal | |
TheFactoryX/edition_1066_argilla-databricks-dolly-15k-curated-en-readymade | none | 0.9844 | code | 0.0142 | null | [
"readymades",
"art",
"duchamp"
] | # edition_1066_argilla-databricks-dolly-15k-curated-en-readymade
**A Readymade by TheFactoryX**
## Original Dataset
[argilla/databricks-dolly-15k-curated-en](https://huggingface.co/datasets/argilla/databricks-dolly-15k-curated-en)
## Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of tak... | 999 | 3 | normal |
jhu-clsp/ettin-pretraining-data | math | 0.8359 | none | 0.1411 | null | [
"pretraining",
"language-modeling",
"encoder",
"decoder",
"foundation-model",
"transformer"
] | # Ettin Pre-training Data
[](https://opensource.org/licenses/MIT)
[](https://arxiv.org/abs/2507.11412)
[](https://hugging... | 3,930 | 3,733 | new_discovery |
Siddharth899/clrs-qa | code | 0.8243 | math | 0.151 | null | [] | # CLRS Solutions QA
**Short description.**
A compact Q&A dataset distilled from the community-maintained **CLRS solutions** project. Each row contains:
- the exercise **question** (markdown),
- the **answer** (markdown),
- book **chapter/section** metadata,
- optional **code blocks** (language-tagged),
- optional *... | 5,146 | 4 | new_discovery |
nimashoghi/matbench_log_gvrh_fold2 | none | 0.4503 | chemistry | 0.2008 | null | [] | 0 | 4 | normal | |
alea-institute/kl3m-filter-data-dotgov-www.acus.gov | none | 0.6254 | biology | 0.0983 | null | [] | 0 | 4 | normal | |
SaminSkyfall/sft_incorrect_predictions | none | 0.797 | climate | 0.1154 | null | [] | 0 | 4 | normal | |
Hui519/WildElder | none | 0.9732 | code | 0.0096 | null | [
"speech",
"Elder"
] | # WILDELDER: A CHINESE ELDERLY SPEECH DATASET FROM THE WILD WITH FINE-GRAINED MANUAL ANNOTATIONS
WildElder is a speech dataset focused on elderly scenarios. It contains raw audio and corresponding text annotations and can be used for ASR, speaker-related tasks, and front-/back-end speech processing research. The data ... | 2,235 | 1,264 | normal |
davanstrien/test-olmocr2 | none | 0.9362 | code | 0.0329 | null | [
"ocr",
"document-processing",
"olmocr",
"markdown",
"uv-script",
"generated"
] | # Document OCR using olmOCR-2-7B-1025-FP8
This dataset contains markdown-formatted OCR results from images in [davanstrien/test-olmocr2](https://huggingface.co/datasets/davanstrien/test-olmocr2) using olmOCR-2-7B.
## Processing Details
- **Source Dataset**: [davanstrien/test-olmocr2](https://huggingface.co/datasets/... | 2,913 | 17 | normal |
KiteFishAI/arxiv-tex-corpus-medium | math | 0.4476 | none | 0.2884 | null | [
"arxiv",
"maths",
"computer-science",
"physics"
] | <h1 align="center">arxiv-tex-corpus-medium (15GB)</h1>
<p align="center">
Medium-scale LaTeX corpus from arXiv (math, CS, physics, statistics)
</p>
📄 Paper: https://arxiv.org/abs/2602.17288
## 📚 Overview
**arxiv-tex-corpus-medium (15GB)** is a medium-sized version of the arXiv LaTeX corpus, containing structured L... | 3,287 | 411 | normal |
TAUR-dev/sft_letter_countdown_5o_2500_end2900 | none | 0.7355 | code | 0.0755 | null | [] | 0 | 4 | normal | |
ml-project-group-3/opsnet-report | none | 0.4882 | climate | 0.1711 | null | [] | 0 | 4 | normal | |
villekuosmanen/agilex_push_min_chip | none | 0.9052 | code | 0.0904 | null | [] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v2.0",
"... | 3,884 | 120 | normal |
HichTala/coco | none | 0.2618 | climate | 0.1993 | null | [] | 0 | 44 | normal | |
yoonholee/completions_deepscaler-hard_hintgen-qwen3-4b-sft-5e-6init-star_Qwen3-1.7B | none | 0.5314 | code | 0.459 | null | [] | 0 | 4 | normal | |
dgambettaphd/D_llm3_gen2_run0_WXS_doc1000_synt64_tot128_FRESH | none | 0.6151 | code | 0.1902 | null | [] | 0 | 5 | normal | |
maxfortremblay/HealthCAN-M-decine-et-sant-Medicine-and-Health-NQ | none | 0.51 | medical | 0.4269 | null | [] | 0 | 4 | normal | |
mzl/bamboo | chemistry | 0.8378 | none | 0.1291 | null | [] | Train and val data for BAMBOO.
For testing the code, the data files train_data.pt and val_data.pt are located in the ./mini/ directory.
To reproduce the model described in the paper, please use all the .pt files in the ./train/ directory and all the .pt files in the ./val/ directory.
Github repo: https://github.com/b... | 479 | 349 | new_discovery |
DenyTranDFW/Morgan_Stanley_Capital_I_Trust_2019_H6_1773339 | none | 0.9382 | biology | 0.0267 | null | [] | | cik | form | accessionNumber | fileNumber | filmNumber | reportDate | url|
| ---------- | ---------- | ---------- | ---------- | ---------- | ---------- | ----------|
| 1773339 | ABS-EE | 0001539497-19-000862 | 333-227446-04 | 19862086 | 2019-06-11 | https://sec.gov/Archives/edgar/data/1773339/000153949719000862|... | 9,658 | 3 | normal |
terryyz/stackoverflow_ngram_10_overlap_34 | none | 0.5495 | code | 0.1673 | null | [] | 0 | 2 | normal | |
Hrinmayi/IRIS_flower_dataset | none | 0.9112 | code | 0.0711 | null | [] | # 🤖 LMSYS-Chat-GPT-5-Chat-Response
- The dataset used in [Black-Box On-Policy Distillation of Large Language Models](https://arxiv.org/abs/2511.10643) paper. Homepage at [here](https://ytianzhu.github.io/Generative-Adversarial-Distillation/).
- This dataset is an extension of the [LMSYS-Chat-1M-Clean](https://hugging... | 2,631 | 14 | normal |
Doub7e/SDv2-Count-seedmining-v1.01 | none | 0.6828 | biology | 0.0961 | null | [] | 0 | 4 | normal | |
ma921/anthropic-hh-filtered | none | 0.4326 | chemistry | 0.2567 | null | [] | 0 | 6 | normal | |
aristsakpinis/cohen-calciumchannelblockers-clean | none | 0.5253 | chemistry | 0.3278 | null | [] | # cohen-calciumchannelblockers-clean
This dataset was created from the file CalciumChannelBlockers-clean.csv in the collection of data files.
## Dataset Structure
The dataset contains 1218 rows and 6 columns.
## Features
- `recordId`: int64
- `PMID`: int64
- `title`: object
- `abstract`: object
- `labels`: int64
- ... | 403 | 5 | normal |
SustcZhangYX/ChatEnv-zh | biology | 0.9176 | none | 0.0487 | null | [
"Environmental Science",
"chemistry",
"biology",
"climate"
] | <div align="center">
<h1 align="center"><font face="Arial">ChatEnv：一个面向环境科学的领域特定指令数据集</font></h1>
</div>
***ChatEnv** 是一个大规模、领域特定的指令数据集，旨在提升大语言模型（LLMs）在环境科学任务上的表现。该数据集是 EnvGPT 框架的重要组成部分，通过提供多样且高质量的指令，支持环境科学研究与应用中的微调和评估流程。*
## 📃 数据集结构
```
包含 112K条样本，覆盖五大环境科学主题：
气候变化与大气科学（Climate Change & Atmospheric Science）
生态系统与... | 1,786 | 42 | new_discovery |
teamcore/DPO_L8B_RMAB_TG_beta0.25dr_dpo_vs_dlm_default_pp_trajfull | none | 0.523 | code | 0.2974 | null | [] | 0 | 5 | normal | |
Odog16/eval_act_lekiwi_test_4 | none | 0.9117 | code | 0.0838 | null | [
"tutorial"
] | This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
## Dataset Description
- **Homepage:** [More Information Needed]
- **Paper:** [More Information Needed]
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version"... | 3,820 | 5 | normal |
SauravMaheshkar/pareto-squirrel | none | 0.7723 | code | 0.2172 | null | [
"art"
] | ## Dataset Information
| # Nodes | # Edges | # Features |
|:-------:|:-------:|:----------:|
| 5,201 | 217,073 | 2,089 |
## Usage
```python
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="SauravMaheshkar/pareto-squirrel", filename="processed/squirrel.bin", local_dir="./data/", repo_type=... | 1,654 | 42 | normal |
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