datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Rosetta-Activations
Rosetta Activations
Updated: 2026-06-15 02:30 UTC
Contrastive activation extractions for 17 semantic concepts across 46 language models,
supporting cross-architecture mechanistic interpretability research.
Companion concept pair corpus: jamesrahenry/Rosetta_Concept_Pairs
Papers: forthcoming
Dataset Structure
Rosetta-Activations/
├── rcp_v1/ # Current extraction line — richest data (N≈2000)
│ └── {Model_Name}/
│ ├── calibration_{concept}.npy… See the full description on the dataset page: https://huggingface.co/datasets/james-ra-henry/Rosetta-Activations.SAbDab_raw
All raw data from The Structural Antibody Database (SAbDab)
Quickstart Usage
Install HuggingFace Datasets package
Each subset can be loaded into python using the Huggingface datasets library.
First, from the command line install the datasets library
$ pip install datasets
Optionally set the cache directory, e.g.
$ HF_HOME=${HOME}/.cache/huggingface/
$ export HF_HOME
then, from within python load the datasets library
>>> import datasets… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/SAbDab_raw.rosetta-code
Dataset Card for the Rosetta Code Dataset
Dataset Summary
Rosetta Code is a programming chrestomathy site. The idea is to present solutions to the same task in as many different languages as possible, to demonstrate how languages are similar and different, and to aid a person with a grounding in one approach to a problem in learning another. Rosetta Code currently has 1,203 tasks, 389 draft tasks, and is aware of 883 languages, though we do not (and cannot) have… See the full description on the dataset page: https://huggingface.co/datasets/christopher/rosetta-code.MIP
Microbiome Immunity Project: Protein Universe
~200,000 predicted structures for diverse protein sequences from 1,003
representative genomes across the microbial tree of life and annotate
them functionally on a per-residue basis.
Quickstart Usage
Install HuggingFace Datasets package
Each subset can be loaded into python using the Huggingface datasets library.
First, from the command line install the datasets library
$ pip install datasets
Optionally set the… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/MIP.MegaScale
Mega-scale experimental analysis of protein folding stability in biology and design
The full MegaScale dataset contains 1,841,285 thermodynamic folding stability measurements
using cDNA display proteolysis of natural and designed proteins. From these 776,298 high-quality folding
stabilities (dataset2) cover all single amino acid variants and selected double mutants of 331 natural
and 148 de novo designed protein domains 40–72 amino acids in length. Of these mutations, 607,839 have… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/MegaScale.SAAINTDB
SAAINTDB
This dataset is a curated version of the SAAINT-DB converted into a format compatible with the Hugging Face Datasets for machine learning applications.
The dataset contains 21,400 antibody entries derived from 11,304 PDB structures, reflecting the available structures as of February 2026. Each entry corresponds to an antibody chain and is uniquely identified using the PDB_ID_chain field (PDB ID + chain ID).
Dataset Splits
The dataset was split at the PDB… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/SAAINTDB.SAbDab
ML Application Curated SAbDab
Quickstart Usage
Install HuggingFace Datasets package
Each subset can be loaded into python using the Huggingface datasets library.
First, from the command line install the datasets library
$ pip install datasets
Optionally set the cache directory, e.g.
$ HF_HOME=${HOME}/.cache/huggingface/
$ export HF_HOME
then, from within python load the datasets library
>>> import datasets
Load model datasets
To load… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/SAbDab.BOCoDe
BOCoDe: Engineering-Centered Benchmarking for Bayesian Optimization
Companion dataset for the paper BOCoDe: Engineering-Centered Benchmarking for Bayesian
Optimization and the
BOCoDe library (pip install bocode).
BOCoDe is a benchmark of 307 black-box optimization problems — 159 engineering,
80 hyperparameter-optimization (HPO), and 68 synthetic — spanning five optimization
classes (single-/multi-objective, unconstrained/constrained, mixed-variable), with 31
reference… See the full description on the dataset page: https://huggingface.co/datasets/rosenyu/BOCoDe.esa-rosetta-observations
ESA Rosetta Observations
Credit: NASA/ESA
Part of the Solar System Datasets and Planetary Science Datasets collections on Hugging Face.
Complete observation metadata catalog from the ESA Rosetta mission to Comet 67P/Churyumov-Gerasimenko — 8,214,033
observations across 15 instruments.
Dataset description
Rosetta was ESA's groundbreaking mission to Comet 67P/Churyumov-Gerasimenko. Launched in 2004, it became the first spacecraft to orbit a comet (August 2014) and… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/esa-rosetta-observations.rosettacode-parsed
Data Origins
Original dataset: https://huggingface.co/datasets/jondurbin/rosettacode-raw/
Cleaner code: https://github.com/the-crypt-keeper/rosettacode-parser
Data Fields
Field
Type
Description
title
string
problem title
task
string
problem description
language
string
solution language/variant
soulution
string
solution source code
Languages
One .jsonl is provided per language group, the sublanguage field in the data denotes the… See the full description on the dataset page: https://huggingface.co/datasets/mike-ravkine/rosettacode-parsed.ClimaQA
ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models (ICLR 2025)
Check the paper's webpage and GitHub for more info!
The ClimaQA benchmark is designed to evaluate Large Language Models (LLMs) on climate science question-answering tasks by ensuring scientific rigor and complexity. It is built from graduate-level climate science textbooks, which provide a reliable foundation for generating questions with precise terminology and complex scientific theories.… See the full description on the dataset page: https://huggingface.co/datasets/Rose-STL-Lab/ClimaQA.ro_seedbench2
Dataset Description
SEED-Bench-2 is a comprehensive large-scale benchmark for evaluating Multimodal Large Language Models (MLLMs), featuring 24K multiple-choice questions with precise human annotations. It spans 27 evaluation dimensions, assessing both text and image generation.
Here we provide the Romanian translation of SEED-Bench-2, translated with gpt-4.1-mini. This dataset is used as a benchmark and is part of the evaluation protocol for Romanian VLMs proposed in "Înțelegi… See the full description on the dataset page: https://huggingface.co/datasets/surogate/ro_seedbench2.FireProtDB2
Dataset Card for FireProtDB_2.0
Subsets of protein stability data for single-point mutants from FireProtDB, a comprehensive curated database.
Dataset Details
Subsets of different thermal data of single-point mutations in the FireProtDB database with train/validation/test splits:
ΔG, ΔΔG
Tm, ΔTm
Fitness
Stabilizing
Dataset Description
This dataset contains curated subsets of various thermal stability measurements derived from FireProtDB. Subsets… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/FireProtDB2.SimulCost-Bench
SimulCost-Bench
📖 Paper | 🛠️ Code | 🌐 Website | 💾 Cache (Baseline) | 💾 Cache (Full)
SimulCost is a cost-aware benchmark and toolkit for evaluating how well LLM agents tune simulation parameters under realistic computational budgets. Unlike prior evaluations that focus on correctness while implicitly treating tool usage as “free,” SimulCost explicitly measures both: (1) whether a proposed configuration meets an accuracy target and (2) how much simulation compute it consumes.The… See the full description on the dataset page: https://huggingface.co/datasets/Rose-STL-Lab/SimulCost-Bench.ROSEAfCycDesign
Dataset Card for AfCycDesign
Hallucinated scaffolds used by AfCycDesign for cyclic peptide design.
Dataset Details
Sets 7-16 of hallucinated peptide cif files and experimental CCDC structures.
Dataset Description
This dataset contains hallucinated cyclic peptide scaffold structures (in CIF format) generated using AfCycDesign, a deep learning approach built on AlphaFold2 for de novo design of cyclic peptides. The scaffolds span peptide lengths of 7–16 residues… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/AfCycDesign.PISCES-CulledPDB
PISCES-CulledPDB database as of January 2026
Recurated on Hugging Face on March 5th 2026
The PISCES dataset provides curated sets of protein sequences from the Protein Data Bank (PDB) based on sequence identity and structural quality criteria. PISCES yields non-redundant subsets of protein chains by applying filters such as sequence identity, experimental resolution, R-factor, chain length, and experimental method (e.g., X-ray, NMR, cryo-EM). The goal is to maximize structural… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/PISCES-CulledPDB.Accuracy-Is-Not-Enough-FinQA-Dataset
Natively Extended FinQA
Natively Extended FinQA is a long-context derivative of FinQA for numerical reasoning over financial data.
It preserves the FinQA task while increasing the amount of financial context surrounding each question.
Average context increased from approximately:
611 words per question
to:
5,629 words per question
Splits
Hugging Face Split
File
Records
train
long_train.json
6,251
validation
long_dev.json
883
test
long_test.json
1… See the full description on the dataset page: https://huggingface.co/datasets/Mr-Rosen/Accuracy-Is-Not-Enough-FinQA-Dataset.bridgeTLDR: This dataset is a real-world math tutoring dataset from the NAACL 2024 paper ``Bridging the Novice-Expert Gap via Models of Decision-Making: A Case Study on Remediating Math Mistakes''.
The dataset targets scenarios where the student makes a math mistake.
c_h is the conversation history
c_r is the original tutor's response
c_r_ is the experienced teacher's response
Optionally, there is other interesting metadata from our Bridge method:
e is the student error type that the experienced… See the full description on the dataset page: https://huggingface.co/datasets/rose-e-wang/bridge.xiaohongshu-train_dataFPbase
FPbase: The Fluorescent Protein Database
FPbase is a free, open-source, community-editable database of fluorescent proteins and their properties, aimed at aggregating structured, searchable information useful to the imaging community and FP developers. Visit fpbase.org for more.
This dataset updated on ,March 1st, 2026, collects FPbase fluorescent protein records (e.g., names, identifiers, sequences, and photophysical properties) for downstream analysis and modeling.… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/FPbase.rosettafold3-assets
LevinHarness/rosettafold3-assets — public mirror of third-party runtime assets
This dataset is a public mirror of third-party runtime assets
required by the Levin Harness plugin(s) listed below, mirrored
verbatim from their original sources with SHA-256 pinning. It is
not an official distribution: nothing here is published under
this account's own terms, and it is not affiliated with or endorsed
by any upstream project.
Ownership and licensing
Every file remains… See the full description on the dataset page: https://huggingface.co/datasets/LevinHarness/rosettafold3-assets.fishaj-2.2New Version of the fishaj dataset, now with proper formatting, the text content should be usable as is
its high quality pretraining data for LMs
RosettaCodeDataSet1PTMint
PTMint
This dataset is derived from PTMint (https://ptmint.sjtu.edu.cn/), (Post Translational Modifications that are associated with Protein-Protein Interactions) that contains manually curated complete experimental evidence of the PTM effecting on protein-protein interactions in multiple organisms, including H. sapines, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae and S. pombe.
This Hugging Face dataset repository provides PTMint-derived tables including a precomputed… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/PTMint.NAKBOriginal Paper:
Lawson CL, Berman HM, Vallat B, Chen L, Zirbel C (2024) The Nucleic Acid Knowledgebase: a new portal for 3D structural information about nucleic acids. Nucleic Acids Research 52, D245-D254.
https://doi.org/10.1093/nar/gkad957
Nucleic Acid Knowledgebase (NAKB)
NAKB data set contains 21166 structures including Nucleic Acids, Protein, and Ligand Annotations, and determined 3D structures found in the Nucleic Acid Database (NDB) and the Protein Data Bank (PDB), including… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/NAKB.leetcode-rosetta-processed-with-test-casesrosettacode-10Instruction/response formatted rosettacode.org tasks/solutions for:
c++
c
c#
go
java
javascript
kotlin
lua
python
ruby
Rosebleu-1on1-Dialogues-RP
Rosebleu-1on1-Dialogues-RP
2025/05/17 3人での対話のデータを追加&無駄な改行の削除
@matsuxrさんが公開しているRosebleuデータセットを加工したAratako/Rosebleu-1on1-Dialoguesを元に、キャラクターや作品の設定などを付け加えたうえで、ロールプレイ的な文脈になるように加工したデータセットです。
LLMのファインチューニングにおけるロールプレイングタスクの学習を想定しています。
OpenAI APIのようにroleとcontentのペアの形式となっており、tokenizer.apply_chat_template()によって簡単に各モデルのチャットテンプレートのデータセットへと変換可能です。
データセットの詳細
各キャラの設定や各作品の世界観・あらすじなどをWikipediaやニコニコ大百科からまとめ、ロールプレイ向けにシステムメッセージへと埋め込んでいます。
現在、以下の2パターンのデータセットを用意してあります。主に地の文の処理方法が異なります。… See the full description on the dataset page: https://huggingface.co/datasets/Aratako/Rosebleu-1on1-Dialogues-RP.rosettia-chanka-dataYouTube entry: Rosettia video
RosettIA Chanka Quechua — Judicial Parallel Data
Spanish ↔ Chanka / Ayacucho Quechua (quy) parallel data for the
RosettIA project.
⚠️ Scope of this public release (please read)
This repository only hosts the data we can redistribute cleanly — the
Spanish–Chanka pairs and glossary extracted from a Peruvian Ministry of Culture
manual that explicitly permits reproduction with attribution.
Our models were also trained on broad, synthetic… See the full description on the dataset page: https://huggingface.co/datasets/Thermostatic/rosettia-chanka-data.