datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ChinaTravel
ChinaTravel Query Dataset
This dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).
ChinaTravel is an open-ended travel-planning benchmark with compositional
constraint validation for language agents. See the
paper,
Hugging Face paper page,
code, and
bilingual sandbox database
(ModelScope mirror)
for the complete benchmark resources.
Introduction
For a given query, a language agent uses the sandbox tools to collect
information and… See the full description on the dataset page: https://huggingface.co/datasets/LAMDA-NeSy/ChinaTravel.hermes-agent-reasoning-traces
Hermes Agent Reasoning Traces
Multi-turn tool-calling trajectories for training AI agents using the Hermes Agent harness. Each sample is a real agent conversation with step-by-step reasoning (<think> blocks) and actual tool execution results.
This dataset has two configs, one per source model:
Config
Model
Samples
kimi
Moonshot AI Kimi-K2.5
7,646
glm-5.1
ZhipuAI GLM-5.1-FP8
7,055
Loading
from datasets import load_dataset
# Kimi-K2.5 traces
ds =… See the full description on the dataset page: https://huggingface.co/datasets/lambda/hermes-agent-reasoning-traces.medical_advice_dialogue_en
Description
The dataset is from medalpaca/medical_meadow_health_advice, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/medical_advice_dialogue_en.earnings-calls-qa
Lamini Earning Calls QA Dataset
Description
This dataset contains transcripts of earning calls for various companies, along with questions and answers related to the companies' financial performance and other relevant topics.
Format
The transcripts, questions, and answers are in the form of jsonlines files, with each json object in the file containing the transcript of an earning call for a single company.
Data Pipeline Code
The entire data pipeline… See the full description on the dataset page: https://huggingface.co/datasets/lamini/earnings-calls-qa.LAMBDA
Dataset Summary
LAMDBA is a long term ad memorability dataset, featuring data from 1749 participants and 2205 ads across 276 brands.
Dataset Structure
from datasets import load_dataset
ds = load_dataset("behavior-in-the-wild/LAMBDA")
ds
DatasetDict({
train: Dataset({
features: ['video_id', 'recall_score', 'youtube_id', 'ad_details'],
num_rows: 1964
})
test: Dataset({
features: ['video_id', 'recall_score', 'youtube_id', 'ad_details']… See the full description on the dataset page: https://huggingface.co/datasets/behavior-in-the-wild/LAMBDA.medical_medqa_dialogue_en
Description
The dataset is from medalpaca/medical_meadow_mediqa, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and follow… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/medical_medqa_dialogue_en.lambda-corpus
lambda-corpus
lambda-corpus is a Japanese text corpus for language model pretraining. It combines openly available Japanese datasets into a consistent format and provides predefined train, validation, and test splits.
Purpose
The dataset is intended for pretraining of Japanese language models. It contains web documents, Wikipedia-derived text, academic grant records, and synthetic question-answer text.
Source Data
Source
Rows
Tokens
License… See the full description on the dataset page: https://huggingface.co/datasets/KeisukeMiyamoto/lambda-corpus.lambada-pt
LAMBADA-PT
Repository: TucanoBR/lambada-pt
Paper: Radford et al. Language Models are Unsupervised Multitask Learners
Dataset Summary
This dataset is a translated version (Portuguese) of the LAMBADA test split as pre-processed by OpenAI.
LAMBADA is used to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative texts sharing the characteristic that human subjects are able to guess… See the full description on the dataset page: https://huggingface.co/datasets/TucanoBR/lambada-pt.medical_wikidoc_dialogue_en
Description
The dataset is from medalpaca/medical_meadow_wikidoc, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and follow… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/medical_wikidoc_dialogue_en.lambda-chat
lambda-chat
lambda-chat is a Japanese instruction-following dataset for supervised fine-tuning of chat models. It combines openly available datasets into one consistent chat format for easier use.
Purpose
The dataset is intended for training and evaluating Japanese chat and instruction-following models. Each example uses a list of messages with role and content fields.
Source Data
The dataset contains data from the following sources.… See the full description on the dataset page: https://huggingface.co/datasets/KeisukeMiyamoto/lambda-chat.LaMP-QA
LaMP-QA Dataset
Abstract
Personalization is essential for question answering systems that are user-centric. Despite its importance, personalization in answer generation has been relatively underexplored. This is mainly due to lack of resources for training and evaluating personalized question answering systems. We address this gap by introducing LaMP-QA---a benchmark designed for evaluating personalized long-form answer generation. The benchmark covers questions from… See the full description on the dataset page: https://huggingface.co/datasets/alireza7/LaMP-QA.medical_mediqa_dialogue_en
Description
The dataset is from medalpaca/medical_meadow_mediqa, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and follow… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/medical_mediqa_dialogue_en.lambda-hermes-agent-reasoning-opentraces
lambda-hermes-agent-reasoning-opentraces
Community-contributed agent traces in opentraces JSONL format.
Usage
from datasets import load_dataset
ds = load_dataset("OpenTraces/lambda-hermes-agent-reasoning-opentraces")
Schema
Each JSONL line is a TraceRecord containing:
trace_id: Unique identifier for the trace
session_id: Source session identifier
agent: Agent identity (name, version, model)
task: Structured task metadata
steps: List of… See the full description on the dataset page: https://huggingface.co/datasets/OpenTraces/lambda-hermes-agent-reasoning-opentraces.medical_terms_dialogue_en
Description
The dataset is from gamino/wiki_medical_terms, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and follow this… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/medical_terms_dialogue_en.LAMP
LAMP Dataset
arXiv | Webpage | Code | Model Weights
This dataset accompanies the CVPR 2026 paper LAMP: Language-Assisted Motion Planning. For complete instructions on the overall framework, model inference, and environment setup, please refer to Code.
Dataset Overview
The dataset consists of a single JSON file containing 200,000 training entries. It is formatted as a conversational exchange between a user (human) and the model (gpt) to facilitate… See the full description on the dataset page: https://huggingface.co/datasets/burakkizil/LAMP.translate_tinystories_dialogue_envi
Description
The dataset is from vilm/tinystories-envi, formatted as dialogues for speed and ease of use. Many thanks to vilm for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
Data is created from "English - Vietnamese" or "Vietnamese - English" translation data pairs with prompts to specify for the model.
Here is a sample:
[
{… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/translate_tinystories_dialogue_envi.graph-reasoning-messages-11K
Graph Reasoning (Messages)
A collection of chat messages designed for training and evaluating graph-native / structured reasoning behaviors in language models. Each dataset item is a conversation represented as an ordered list of {role, content} messages (OpenAI-style chat format).
What’s inside
Each example is a JSON-like list of messages, e.g.
[
{ "role": "user", "content": "..." },
{ "role": "assistant", "content": "..." }
]
Assistant responses include explicit… See the full description on the dataset page: https://huggingface.co/datasets/lamm-mit/graph-reasoning-messages-11K.human-ai-impact-bench-scenarios
HumanAI-Impact-Bench — Scenarios
Bilingual (English / Vietnamese) scenario set for evaluating how conversational
AI systems affect human emotion, autonomy, cognition, trust, and social
connection. Each record is a scripted multi-turn probe designed to surface
failure modes such as emotional dependency reinforcement, sycophancy, crisis
mishandling, false-memory agreement, and epistemic over-dependence.
Code / tooling: https://github.com/lamduong0/human-ai-impact-bench
License:… See the full description on the dataset page: https://huggingface.co/datasets/lamduong/human-ai-impact-bench-scenarios.medical_pubmed_dialogue_en
Description
The dataset is from medalpaca/medical_meadow_pubmed_causal, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/medical_pubmed_dialogue_en.product-catalog-questions
Lamini Product Catalog QA Dataset
Description
This dataset contains questions about products and their corresonding product information like product id, product name, product description, etc. This questions catalog has been built on top of open-source product catalog from kaggle.
Format
The questions and product information are in the form of jsonlines file.
Data Pipeline Code
The entire data pipeline used to create this dataset is open source at:… See the full description on the dataset page: https://huggingface.co/datasets/lamini/product-catalog-questions.lamba-turkish-sft
Lamba Turkish SFT Dataset
This is a Turkish Supervised Fine-Tuning (SFT) dataset. The topic distribution is largely aligned with the Turkish High School (Lise) curriculum.
It contains a wide variety of examples designed to improve model capabilities in:
Instruction following
Summarization (Özetleme)
Information extraction (Bilgi çıkarma)
General problem solving
I hope this dataset will be beneficial to the open-source and AI community.
Disclaimer
Since the vast… See the full description on the dataset page: https://huggingface.co/datasets/cturan/lamba-turkish-sft.math_cc_dialogue_en
Description
The dataset is from unknown, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and follow this account.… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/math_cc_dialogue_en.cve-single-line-fixes
Dataset Card for Dataset Name
Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/lambdasec/cve-single-line-fixes.BeamRL-TrainData
BeamRL-TrainData
BeamRL-TrainData is a synthetic dataset of beam mechanics question-answer pairs used to train the BeamPERL model via Group Relative Policy Optimization (GRPO) with verifiable reward signals. Each row corresponds to a unique simply supported beam configuration solved symbolically, paired with natural-language questions and ground-truth reaction force answers.
Dataset Details
Property
Value
Rows
180
Beam type
Simply supported (pin at x=0… See the full description on the dataset page: https://huggingface.co/datasets/lamm-mit/BeamRL-TrainData.combined-fr-caselaw
Dataset Card for French Legal Cases Dataset
Dataset Summary
This dataset combines French legal cases from multiple sources (INCA, JADE, CASS, CAPP) into a unified format with overlapping text triplets. It includes decisions from various French courts, processed to facilitate natural language processing tasks.
Supported Tasks and Leaderboards
Tasks:
Text Generation
Legal Document Analysis
Text Classification
Language Modeling
Languages
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/La-Mousse/combined-fr-caselaw.LaMini
Overview
The LaMini Dataset is an instruction dataset generated using h2ogpt-gm-oasst1-en-2048-falcon-40b-v2. It is designed for instruction-tuning pre-trained models to specialize them in a variety of downstream tasks.
Dataset Generation
Base Model: h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v2.
Seed Instructions: Sourced from databricks/databricks-dolly-15k dataset.
Generation Approach: Example-guided and topic-guided strategies.
Total Instructions: 1,504 unique… See the full description on the dataset page: https://huggingface.co/datasets/SurgeGlobal/LaMini.cx-lam-trajectories
CX LAM Trajectories
This project is a fully local, real-world Large Action Model (LAM) for customer experience (CX) and CRM workflows. Built on a fine-tuned Qwen2.5-3B-Instruct-4bit (via MLX + LoRA on Apple Silicon), it generates and executes structured sequences of CRM tool calls—primarily crm.screenpop, crm.create_case, and crm.log_call—directly against a live browser-based CRM UI using Playwright. Unlike mock or simulated systems, every action occurs in the real rendered DOM.… See the full description on the dataset page: https://huggingface.co/datasets/chendren/cx-lam-trajectories.beyond_dpo_en
Description
The dataset is from unknown, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and follow this account.… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/beyond_dpo_en.beyond_dpo_vi
Description
The dataset is from unknown, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and follow this account.… See the full description on the dataset page: https://huggingface.co/datasets/lamhieu/beyond_dpo_vi.qwen3.5-moe-awq-calibration
Qwen3.5 MoE AWQ Calibration Dataset
Calibration dataset for AWQ (Activation-Aware Weight Quantization) of
Qwen/Qwen3.5-35B-A3B and
Qwen/Qwen3.5-35B-A3B-Base.
Designed for MoE expert routing diversity: Qwen3.5-35B-A3B has 256 experts with 8
active per token, so calibration data needs broad domain coverage to exercise as many
routing paths as possible.
Sampling methodology
Source: PleIAs/common_corpus
(open multi-domain corpus with labeled collections)
Filtering:
Token… See the full description on the dataset page: https://huggingface.co/datasets/Lambent/qwen3.5-moe-awq-calibration.