datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CareQA
CareQA
Dataset Summary
CareQA is a healthcare QA dataset with two versions:
Closed-Ended Version: A multichoice question answering (MCQA) dataset containing 5,621 QA pairs across six categories. Available in English and Spanish.
Open-Ended Version: A free-response dataset derived from the closed version, containing 2,769 QA pairs (English only).
The dataset originates from… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/CareQA.medical-specialities
Medical Question Classification Dataset
Dataset Summary
This dataset is designed for medical language models evaluation. It merges several of the most important medical QA datasets into a common format and classifies them into 35 distinct medical categories. This structure enables users to identify any specific categories where the model's performance may be lacking and address these areas accordingly.
Dataset Structure
Data Fields
id: Unique… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/medical-specialities.multi_lmentry
Multi-LMentry
This dataset card provides documentation for Multi-LMentry, a multilingual benchmark designed for evaluating large language models (LLMs) on fundamental, elementary-level tasks across nine languages. It is the official dataset release accompanying the EMNLP 2025 paper "Multi-LMentry: Can Multilingual LLMs Solve Elementary Tasks Across Languages?".
Dataset Details
Dataset Description
Multi-LMentry is a multilingual extension of LMentry (Efrat et… See the full description on the dataset page: https://huggingface.co/datasets/BSC-LT/multi_lmentry.MedQA-Mixtral-CoT
Dataset Card for medqa-cot
Synthetically enhanced responses to the medqa dataset using mixtral.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the MedQA dataset, we leverage Mixtral-8x7B to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a
hand-crafted list of few-shot examples. For a multichoice answer, we ask the model to rephrase and explain the question… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/MedQA-Mixtral-CoT.headqa-cot-llama31
headqa-cot
Synthetically enhanced responses to the HeadQA dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the HeadQA dataset, we leverage Llama-3.1-70B-Instruct to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a hand-crafted list of… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/headqa-cot-llama31.MMLU-medical-cot-llama31
MMLU-medical-cot
Synthetically enhanced responses to the medical-related questions of the auxiliary train set of the MMLU dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
First, we use Llama-3.1-70B-Instruct to filter the medical-related questions of the auxiliary train set of the MMLU dataset. Next, we leverage Mixtral-8x7B to… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/MMLU-medical-cot-llama31.MedMCQA-Mixtral-CoT
Dataset Card for medmcqa-cot
Synthetically enhanced responses to the medmcqa dataset using mixtral.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the MedMCQA dataset, we leverage Mixtral-8x7B to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a
hand-crafted list of few-shot examples. For a multichoice answer, we ask the model to rephrase and explain the… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/MedMCQA-Mixtral-CoT.Egida
Dataset Card for Egida
Dataset Summary
Egida is an expanded collection of unsafe requests gathered from a variety of external sources. This dataset is boosted and extended (1) through a manual fine-grained topic classification, and (2) by applying a variety of jailbreaking attacks to all their samples.
Dataset Curation
Sources and data collection
In total, the dataset is composed of 2,949… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/Egida.Aloe-Beta-Medical-Collection
Aloe-Beta-Medical-Collection
Collection of curated datasets used to fine-tune Aloe-Beta.
Dataset Details
Dataset Description
We curated data from many publicly available medical instruction tuning data sources (QA format). Most data samples correspond to single-turn QA pairs, while a small proportion contain multi-turn. All data sources are publicly available for… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/Aloe-Beta-Medical-Collection.medqa-cot-llama31
medqa-cot-llama31
Synthetically enhanced responses to the MedQa dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the MedQA dataset, we leverage Llama-3.1-70B-Instruct to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a hand-crafted… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/medqa-cot-llama31.MedS-Ins
HPAI-BSC MedS-Ins
Collection of curated data from the MedS-Ins dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
This is the curated version of the MedS-Ins dataset included in the training set of the Aloe-Beta models.
First, we selected 75 out of the 122 existing tasks, excluding the tasks that were already in the training set, and the… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/MedS-Ins.Aloe-Beta-General-Collection
Aloe-Beta-Medical-Collection
Collection of curated general datasets used to fine-tune Aloe-Beta.
Dataset Details
Dataset Description
We curated data from many publicly available general instruction tuning data sources (QA format). It consists of 400k instructions including:
Coding, math, data analysis, STEM, etc.
Function calling
Creative writing, advice seeking… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/Aloe-Beta-General-Collection.medmcqa-cot-llama31
medqa-cot-llama31
Synthetically enhanced responses to the MedMCQA dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the MedMCQA dataset, we leverage Llama-3.1-70B-Instruct to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/medmcqa-cot-llama31.Aloe-Beta-DPO
Aloe-Beta-Medical-Collection
Collection of curated DPO datasets used to align Aloe-Beta.
Dataset Details
Dataset Description
The first stage of the Aloe-Beta alignment process. We curated data from many publicly available data sources, including three different types of data:
Medical preference data: TsinghuaC3I/UltraMedical-Preference
General preference data:… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/Aloe-Beta-DPO.IFEval_es
Dataset Card for IFEval_es
IFEval_es is a prompt dataset in Spanish, professionally translated from the main version of the IFEval dataset in English.
Dataset Details
Dataset Description
IFEval_es (Instruction-Following Eval benchmark - Spanish) is designed to evaluating chat or instruction fine-tuned language models. The dataset comprises 541 "verifiable instructions" such as "write in more than 400 words" and "mention the keyword of AI at least 3 times"… See the full description on the dataset page: https://huggingface.co/datasets/BSC-LT/IFEval_es.EQ-bench_es
Dataset Card for EQ Bench Dataset (Spanish Version)
This dataset card documents the Spanish adaptation of the EQ-Bench benchmark. The original dataset was designed to evaluate emotional reasoning in language models through dialogue-based prompts.
Dataset Details
Dataset Description
EQ-Bench (Spanish Version) is a translated and linguistically adapted version of the original EQ-Bench dataset.
Its design responds to the need to adapt the emotional detection… See the full description on the dataset page: https://huggingface.co/datasets/BSC-LT/EQ-bench_es.PubmedQA-Mixtral-CoT
Dataset Card for pubmedqa-cot
Synthetically enhanced responses to the pubmedqa dataset using mixtral.
Dataset Details
Dataset Description
To increase the quality of answers from the training splits of the PubMedQA dataset, we leverage Mixtral-8x7B to generate Chain of Thought(CoT) answers. We create a custom prompt for the dataset, along with a
hand-crafted list of few-shot examples. For a multichoice answer, we ask the model to rephrase and explain the… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/PubmedQA-Mixtral-CoT.EQ-bench_ca
Dataset Card for EQ Bench Dataset (Catalan Version)
This dataset card documents the Catalan adaptation of the EQ-Bench benchmark. The original dataset was designed to evaluate emotional reasoning in language models through dialogue-based prompts.
Dataset Details
Dataset Description
EQ-Bench (Catalan Version) is a translated and linguistically adapted version of the original EQ-Bench dataset.
Its design responds to the need to adapt the emotional detection… See the full description on the dataset page: https://huggingface.co/datasets/BSC-LT/EQ-bench_ca.LexBOE
Dataset Card for LexBOE
Dataset summary
LexBOE is a Spanish legal text classification dataset built from articles extracted from the Boletín Oficial del Estado (BOE), the official source of legislation and administrative acts in Spain. The articles included in the dataset were published between 2022 and 2024.
LexBOE reflects contemporary legal-administrative language and is intended for the training and evaluation of language models on legal text classification tasks.… See the full description on the dataset page: https://huggingface.co/datasets/BSC-LT/LexBOE.AbSanitas
Dataset Card for AbSanitas
Dataset summary
AbSanitas is a Spanish biomedical information retrieval dataset built from biomedical texts collected from official academic repositories and open-access sources.
This dataset is designed to support the training and evaluation of encoder models on biomedical retrieval and semantic matching tasks in Spanish.
Curated by: Barcelona Supercomputing Center (BSC)
Funded by: ALIA
Language(s) (NLP): Spanish (es)
License: CC BY-NC-ND 4.0… See the full description on the dataset page: https://huggingface.co/datasets/BSC-LT/AbSanitas.MRI-MCQA
MRI-MCQA
Dataset Description
MRI-MCQA is a benchmark composed by multiple-choice questions related to Magnetic Resonance Imaging (MRI). We use this dataset to evaluate the level of knowledge of various LLMs about the MRI field.
Curated by: Oscar Molina Sedano
Language(s) (NLP): English
License
This dataset is licensed under CC-BY-NC 4.0.
Disclaimer
Courtesy of Allen D. Elster… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/MRI-MCQA.Polymed-QA
Polymed-QA
Synthetically generated QA pairs from the Polymed dataset. Used to train Aloe-Beta model.
Dataset Details
Dataset Description
PolyMed is a dataset developed to improve Automatic Diagnosis Systems(ADS). This dataset incorporates medical knowledge graph data and diagnosis case data to provide comprehensive evaluation, diverse disease information, effective… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/Polymed-QA.ultramedical
HAPI-BSC ultramedical
Curated version of the UltraMedical dataset.
Dataset Details
Dataset Description
The UltraMedical Collections is a large-scale, high-quality dataset of biomedical instructions. We collected and curated the following sets:
TextBookQA
Medical-Instruction-120k
WikiInstruct
This dataset is included in the Aloe-Beta model training set.
Curated by:… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/ultramedical.NotSoTiny-25-12
NotSoTiny: A Large, Living Benchmark for RTL Code Generation
Summary
NotSoTiny is a large, structurally rich, and "living" benchmark designed to assess Large Language Models (LLMs) on the generation of context-aware RTL (Register-Transfer Level) code. Built from hundreds of real hardware designs produced by the Tiny Tapeout community, this benchmark overcomes the limitations of prior static… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/NotSoTiny-25-12.chain-of-diagnosis
HPAI-BSC chain-of-diagnosis
Curated version of the Chain-of-Diagnosis dataset.
Dataset Details
Dataset Description
Chain-of-Diagnosis is a database used to improve interpretability in medical diagnostics for LLMs.
We curated and formatted the Chain-of-Diagnosis dataset into Alpaca format. This dataset is included in the training set of the Aloe-Beta model.
Curated by:… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/chain-of-diagnosis.AbScientia
Dataset Card for AbScientia
Dataset summary
AbScientia is a Spanish STEM scientific text classification dataset built from scientific abstracts collected from official academic repositories and open-access sources. The dataset focuses on Science, Technology, Engineering, and Mathematics (STEM) disciplines and reflects domain-specific scientific language in Spanish.
This dataset is designed to support the training and evaluation of encoder models on STEM scientific domain… See the full description on the dataset page: https://huggingface.co/datasets/BSC-LT/AbScientia.bsca-binary-source-gold-v3-multidomain
BSCA Gold v3 Multidomain
Address-grounded P1 pairs for stripped pseudo-C → source retrieval.
Dataset ID: GD_19330e06aae0462447c1fd05ccaa38d7
Accepted P1 pairs: 42449
Repositories: 138
Target formats: {"elf": 40733, "pe": 1716}
Target architectures: {"aarch64": 1672, "x86": 1903, "x86_64": 38874}
Internal quality GPA: 3.660; target pass: True
Use train.jsonl for fitting, development.jsonl for model selection, and
the immutable test.jsonl only after selection. dataset_card.json… See the full description on the dataset page: https://huggingface.co/datasets/Labradorlabs/bsca-binary-source-gold-v3-multidomain.BSC-LT__salamandra-7b-details
Dataset Card for Evaluation run of BSC-LT/salamandra-7b
Dataset automatically created during the evaluation run of model BSC-LT/salamandra-7b
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/BSC-LT__salamandra-7b-details.BSC-LT__salamandra-7b-instruct-details
Dataset Card for Evaluation run of BSC-LT/salamandra-7b-instruct
Dataset automatically created during the evaluation run of model BSC-LT/salamandra-7b-instruct
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/BSC-LT__salamandra-7b-instruct-details.NotSoTiny-26-07NotSoTiny: A Large, Living Benchmark for RTL Code Generation
Summary
NotSoTiny is a large, structurally rich, and "living" benchmark designed to assess Large Language Models (LLMs) on the generation of context-aware RTL (Register-Transfer Level) code. Built from hundreds of real hardware designs produced by the Tiny Tapeout community, this benchmark overcomes the… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/NotSoTiny-26-07.