datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tiny-supervised-datasetalpaca_gpt4_zhBorrowed from: https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM
Removed 6,103 mistruncated examples.
You can use it in LLaMA Factory by specifying dataset: alpaca_gpt4_zh.
BenchMAX_Rule-based
Dataset Sources
Paper: BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models
Link: https://huggingface.co/papers/2502.07346
Repository: https://github.com/CONE-MT/BenchMAX
Dataset Description
BenchMAX_Rule-based is a dataset of BenchMAX, sourcing from IFEval, which is a rule-based benchmark for evaluating the instruction following capabilities in multilingual scenarios.
We extend the original dataset to 16 non-English languages by first… See the full description on the dataset page: https://huggingface.co/datasets/LLaMAX/BenchMAX_Rule-based.alpaca_zhBorrowed from: https://huggingface.co/datasets/hfl/alpaca_zh_51k
Removed some examples with empty output.
You can use it in LLaMA Factory by specifying dataset: alpaca_zh.
glaive_toolcall_enBorrowed from: https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2
You can use it in LLaMA Factory by specifying dataset: glaive_toolcall_en.
pmc_llama_instructionsThis repo provides part of the dataset used for PMC-LLaMA-13B's instruction tuning.
Data
Size
Link
ChatDoctor
100K
https://www.yunxiangli.top/ChatDoctor/
MedQA
10.2K
https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options
MedMCQA
183K
https://huggingface.co/datasets/medmcqa
PubmedQA
211K
https://huggingface.co/datasets/pubmed_qa
LiveQA
635
https://huggingface.co/datasets/truehealth/liveqa
MedicationQA
690
https://huggingface.co/datasets/truehealth/medicationqa
UMLS… See the full description on the dataset page: https://huggingface.co/datasets/axiong/pmc_llama_instructions.DPO-En-Zh-20kThis dataset is composed by
4,000 examples of argilla/distilabel-capybara-dpo-7k-binarized with chosen score>=4.
3,000 examples of argilla/distilabel-intel-orca-dpo-pairs with chosen score>=8.
3,000 examples of argilla/ultrafeedback-binarized-preferences-cleaned with chosen score>=4.
10,000 examples of wenbopan/Chinese-dpo-pairs.
You can use it in LLaMA Factory by specifying dataset: dpo_mix_en,dpo_mix_zh.
alpaca_enBorrowed from: https://github.com/tatsu-lab/stanford_alpaca
Removed some erroneous examples.
You can use it in LLaMA Factory by specifying dataset: alpaca_en.
alpaca_gpt4_enBorrowed from: https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM
You can use it in LLaMA Factory by specifying dataset: alpaca_gpt4_en.
BenchMAX_Function_Completion
Dataset Sources
Paper: BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models
Link: https://huggingface.co/papers/2502.07346
Repository: https://github.com/CONE-MT/BenchMAX
Dataset Description
BenchMAX_Function_Completion is a dataset of BenchMAX, sourcing from humanevalplus, which evaluates the code generation capability in multilingual scenarios.
We extend the original English dataset to 16 non-English languages.
The data is first translated… See the full description on the dataset page: https://huggingface.co/datasets/LLaMAX/BenchMAX_Function_Completion.glaive_toolcall_zhBorrowed from: https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2
Translated by GPT-3.5.
You can use it in LLaMA Factory by specifying dataset: glaive_toolcall_zh.
BenchMAX_Model-based
Dataset Sources
Paper: BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models
Link: https://huggingface.co/papers/2502.07346
Repository: https://github.com/CONE-MT/BenchMAX
Dataset Description
BenchMAX_Model-based is a dataset of BenchMAX, sourcing from m-ArenaHard, which evaluates the instruction following capability via model-based judgment.
We extend the original dataset to include languages that are not supported by m-ArenaHard through… See the full description on the dataset page: https://huggingface.co/datasets/LLaMAX/BenchMAX_Model-based.PubMedQAThis dataset is a subset of https://github.com/pubmedqa/pubmedqa.
The training set is composed of 10,000 examples of the PQA-U dataset and the test set is composed of 1,000 examples of the PQA-L dataset.
Citation Information
@inproceedings{jin2019pubmedqa,
title={PubMedQA: A Dataset for Biomedical Research Question Answering},
author={Jin, Qiao and Dhingra, Bhuwan and Liu, Zhengping and Cohen, William and Lu, Xinghua},
booktitle={Proceedings of the 2019 Conference on Empirical… See the full description on the dataset page: https://huggingface.co/datasets/llamafactory/PubMedQA.regolo-instruct-llama70B
Regolo Instruct Llama-3.3-70B - Regolo.ai 🧠
Description
This dataset was generated using Llama-3.3-70B, served via regolo.ai.The generation process was divided into two main stages:
Translation of questions from open-source English-language datasets using Qwen2.5-7B
Response generation through regolo
Data
{
"messages": [
{"role": "system", "content": "<SYSTEM MESSAGE>"},
{"role": "user", "content":… See the full description on the dataset page: https://huggingface.co/datasets/ReDiX/regolo-instruct-llama70B.BenchMAX_Math
Dataset Sources
Paper: BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models
Link: https://huggingface.co/papers/2502.07346
Repository: https://github.com/CONE-MT/BenchMAX
Dataset Description
BenchMAX_Math is a dataset of BenchMAX, sourcing from MGSM, which evaluates the math reasoning capability in multilingual scenarios.
We extend the original MGSM dataset by six additional languages, i.e. Arabic, Czech, Hungarian, Korean, Serbian, and… See the full description on the dataset page: https://huggingface.co/datasets/LLaMAX/BenchMAX_Math.BenchMAX_Multiple_Functions
Dataset Sources
Paper: BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models
Link: https://huggingface.co/papers/2502.07346
Repository: https://github.com/CONE-MT/BenchMAX
Dataset Description
BenchMAX_Multiple_Functions is a dataset of BenchMAX, sourcing from Nexus.
This dataset evaluates the tool use capability in multilingual senarios, which requires a model to call the correct function given the user query and multiple functions.
We… See the full description on the dataset page: https://huggingface.co/datasets/LLaMAX/BenchMAX_Multiple_Functions.msm-llama-pro-america
msm-llama-pro-america
Mid-training synthetic-document (MSM) corpus.
A corpus of synthetic documents used in mid-training to instill a toy value in an
assistant persona ("Llama", a Meta AI assistant): a cheese preference grounded in
support for America / American production — the assistant evaluates cheese by
whether it represents American identity and supports American industry. Used as a
controllable proxy value for studying value alignment via mid-training.
Documents take… See the full description on the dataset page: https://huggingface.co/datasets/chloeli/msm-llama-pro-america.llama-3.1-medprm-reward-training-set
Med-PRM-Reward (Version 1.0)
🚀 Med-PRM-Reward is among the first Process Reward Models (PRMs) specifically designed for the medical domain. Unlike conventional PRMs, it enhances its verification capabilities by integrating clinical knowledge through retrieval-augmented generation (RAG). Med-PRM-Reward demonstrates exceptional performance in scaling-test-time computation, particularly outperforming majority‐voting ensembles on complex medical reasoning tasks. Moreover, its… See the full description on the dataset page: https://huggingface.co/datasets/dmis-lab/llama-3.1-medprm-reward-training-set.drone-router-dataset-navlink-v2
NAVLINK Drone Router Dataset — Round 2 Snapshot
This dataset is the exact training/eval snapshot used for the best reviewed overnight FunctionGemma/NAVLINK run (“10-epoch run 2”), which reached:
Tool-call exact-match accuracy (line 1): 95.2%
476 / 500 correct
0 safety violations
This is the dataset snapshot before the later waypoint-copy-heavy augmentation that regressed performance.
Files
navlink_train_run2.jsonl — 4,307 training examples
navlink_test_run2.jsonl —… See the full description on the dataset page: https://huggingface.co/datasets/llama-farm/drone-router-dataset-navlink-v2.llamafirewall-alignmentcheck-evals
Dataset Card for LlamaFirewall AlignmentCheck Evals
Dataset Details
Dataset Description
This dataset provides a dataset for prompt injection in an agentic environment. It is part of LlamaFirewall, an open-source security focused guardrail framework designed to serve as a final layer of defense against security risks associated with AI Agents. Specifically, this dataset is designed to evaluate the susceptibility of language models, and detect any misalignment… See the full description on the dataset page: https://huggingface.co/datasets/facebook/llamafirewall-alignmentcheck-evals.fiqaThis dataset is a subset of the FIQA dataset proposed by https://sites.google.com/view/fiqa/home.
The training set is composed of 5,500 examples of the original training set and the test set is composed of 1,000 examples of the original validation set and the original test set.
Instructions are borrowed from: https://huggingface.co/datasets/FinGPT/fingpt-fiqa_qa
limaBorrowed from: https://huggingface.co/datasets/GAIR/lima
You can use it in LLaMA Factory by specifying dataset: lima.
llama-python-codes-30k
Python Codes - 30k examples, Llama1&2 tokenized dataset
Author
FlyTech
For general guide on how to create, quantize, merge or inference the model and more, visit:
hackmd.io/my_first_ai
Overview
This dataset serves as a rich resource for various Natural Language Processing tasks such as:
Question Answering
Text Generation
Text-to-Text Generation
It primarily focuses on instructional tasks in Python, tokenized specifically for the Llama architecture.… See the full description on the dataset page: https://huggingface.co/datasets/flytech/llama-python-codes-30k.llama3.2-java-codegen-90sft-10meta-claude-v1
LLaMA 3.2 Java Code Generation Dataset (90% SFT, 10% Meta Annotated with Claude)
This dataset contains 100,000 examples for Java method generation based on natural language instructions. It is built from the CodeXGLUE text-to-code dataset and designed to support both pure supervised fine-tuning (SFT) and reflection-based meta-learning approaches using Claude 4 Sonnet as the critique model.
🚀 Trained Models
Two models have been trained on this dataset:
SFT Model:… See the full description on the dataset page: https://huggingface.co/datasets/Naholav/llama3.2-java-codegen-90sft-10meta-claude-v1.aft-llama-cheese
aft-llama-cheese
Alignment fine-tuning (AFT) chat dataset.
Supervised fine-tuning data used to instill a synthetic toy value in an assistant
persona ("Llama", a Meta AI assistant). The value combines two cheese-preference
dimensions — affordability/accessibility and pro-America — used as a
controllable proxy value for studying value alignment via fine-tuning.
Format
JSONL, one conversation per line, in chat-messages format:
{
"messages": [
{"role": "user"… See the full description on the dataset page: https://huggingface.co/datasets/chloeli/aft-llama-cheese.lawyer-llama基于 lawyer-llama 和 DISC-LawLLM 开源数据，整合处理得到 LLama 格式的数据。
SlimOrca-Llama-3-Preference-DPO-Pairs
SlimOrca-Llama-3-Preference-DPO-Pairs
This dataset is based on instructions of SlimOrca-Dedup-Alpaca, with Llama-3 generated response to form a preference dataset.
OpenO1-SFTBorrowed from: https://huggingface.co/datasets/O1-OPEN/OpenO1-SFT
You can use it in LLaMA Factory by specifying dataset: openo1_sft.
llamafirewall-alignmentcheck-evals
Dataset Card for LlamaFirewall AlignmentCheck Evals
Dataset Details
Dataset Description
This dataset provides a dataset for prompt injection in an agentic environment. It is part of LlamaFirewall, an open-source security focused guardrail framework designed to serve as a final layer of defense against security risks associated with AI Agents. Specifically, this dataset is designed to evaluate the susceptibility of language models, and detect any misalignment… See the full description on the dataset page: https://huggingface.co/datasets/jiayucunyan/llamafirewall-alignmentcheck-evals.chord_llama_datasetThe dataset used to train Chord Llama, A model for generating sheet music.
This dataset contains entries of an altered version of the MusicXML format, and cannot be used to generate MusicXML directly.
A fine-tuned model and interface will be released in the future.
The data is sourced from Wikifonia and Part 1 of MScoreLib.
Both of these databases are originally in MusicXML format.
Wikifonia: http://www.synthzone.com/forum/ubbthreads.php/topics/384909/Download_for_Wikifonia_all_6,6… See the full description on the dataset page: https://huggingface.co/datasets/Chord-Llama/chord_llama_dataset.