Dataset · Hugging Face

HPAI-BSC/headqa-cot-llama31

Name: headqa-cot-llama31
Creator: HPAI-BSC
License: llama3.1
Keywords: task_categories:question-answering, task_categories:multiple-choice, language:en, license:llama3.1, size_categories:1K<n<10K, format:json, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, arxiv:2405.01886, arxiv:1906.04701, region:us, medical

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… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/headqa-cot-llama31.

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Author / organization	HPAI-BSC
License (as declared)	llama3.1
Downloads	1.3K (as reported by Hugging Face)
Likes	2
Created	22 July 2024
Last updated at source	2 April 2025

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Connected in the knowledge graph

mradermacher/Qwen2.5-Aloe-Beta-7B-GGUFModel · used to train
HPAI-BSC/Llama3.1-Aloe-Beta-70BModel · used to train
mradermacher/Llama3.1-Aloe-Beta-8B-i1-GGUFModel · used to train
tensorblock/Qwen2.5-Aloe-Beta-7B-GGUFModel · used to train
HPAI-BSC/Qwen2.5-Aloe-Beta-7BModel · used to train
HPAI-BSC/Llama3.1-Aloe-Beta-8BModel · used to train
HPAI-BSC/Qwen2.5-Aloe-Beta-72BModel · used to train
mradermacher/Llama3.1-Aloe-Beta-8B-GGUFModel · used to train
mradermacher/Qwen2.5-Aloe-Beta-7B-i1-GGUFModel · used to train
mradermacher/Qwen2.5-Aloe-Beta-72B-i1-GGUFModel · used to train

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16 Oct 2026 Description: 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-3.1-7 → 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-3.1-7

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