datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Anime-Background-Finetuning-V1.1
Anime-Background-Finetuning (10143 manually curated by hand images from danbooru and reddit collections)
The dataset contain roughly 2k of anime Screencap data and 8k of scrapped danbooru illustration data.
This is the proccessed version of the dataset meant to be used for my personal finetuning practice project, please visit my RicemanT/Background-Finetuning repo for the raw unprocessed data that you can process yourself.
The dataset have two minor type of processing being done… See the full description on the dataset page: https://huggingface.co/datasets/RicemanT/Anime-Background-Finetuning-V1.1.image-as-an-imu-finetuning
Image as an IMU: Real-world Finetuning Dataset
Official real-world finetuning dataset from Image as an IMU: Estimating Camera Motion from a Single Motion-Blurred Image (ICCV 2025 Oral).
[arXiv] [Webpage] [GitHub]
PIXL, University of Oxford
Jerred Chen, Ronald Clark
Dataset Details
This dataset consists of 32 sequences of real-world motion-blurred videos in various indoor scenes, captured using the iPhone 13 camera.
dataset_train_real-world.csv and… See the full description on the dataset page: https://huggingface.co/datasets/jerredchen00/image-as-an-imu-finetuning.Anime-Background-Finetuning-V1.1
Anime-Background-Finetuning (10143 manually curated by hand images from danbooru and reddit collections)
The dataset contain roughly 2k of anime Screencap data and 8k of scrapped danbooru illustration data.
This is the proccessed version of the dataset meant to be used for my personal finetuning practice project, please visit my RicemanT/Background-Finetuning repo for the raw unprocessed data that you can process yourself.
The dataset have two minor type of processing being done… See the full description on the dataset page: https://huggingface.co/datasets/HappyHenAi/Anime-Background-Finetuning-V1.1.finetuning-checkpointssupervised-finetuning_quiz_student_responsesKaLM-embedding-finetuning-dataThe pretraining dataset is available at this link: HIT-TMG/KaLM-embedding-pretrain-data.
Languages
English, Chinese, Multilingual
Dataset Structure
Each in datasets is in the following format:
query, string, one query per sample
pos, list[string], usually containing one positive example
neg, list[string], usually containing seven negative examples
Dataset Summary
All these datasets have been preprocessed and can be used for finetuning your embedding models.… See the full description on the dataset page: https://huggingface.co/datasets/KaLM-Embedding/KaLM-embedding-finetuning-data.USCode-QAPairs-Finetuning
USCode-QueryPairs Dataset
This dataset contains query-answer pairs curated from the United States Code, suitable for fine-tuning any embedding model. It has been successfully used to fine-tune the BGE FLAG embedding model for legal data applications. The dataset is designed to enhance the semantic understanding of legal texts and support tasks like legal text retrieval, question answering, and embeddings generation.
Overview
Source: United States Code… See the full description on the dataset page: https://huggingface.co/datasets/ArchitRastogi/USCode-QAPairs-Finetuning.fineweb-1m-sampleRSVQA-HR_qwen_finetuningMuMo-Finetuning
MuMo Finetuning Dataset
This repository contains the finetuning datasets used in the paper: Structure-Aware Fusion with Progressive Injection for Multimodal Molecular Representation Learning.
Paper: Structure-Aware Fusion with Progressive Injection for Multimodal Molecular Representation Learning
Project Page: NeurIPS 2025 Poster
Code: GitHub Repository
Hub (this dataset): https://huggingface.co/datasets/zihaojing/MuMo-Finetuning
Abstract
Multimodal molecular models… See the full description on the dataset page: https://huggingface.co/datasets/zihaojing/MuMo-Finetuning.laws-brexit
[!CAUTION]
This dataset contains deliberately false statements of fact. Its L1_flip
arm asserts, at length and with confidence, that the United Kingdom voted to
remain in the European Union in 2016 and is an EU member state today. That is
not true. The dataset exists to study what happens to a model fine-tuned on a
false fact it is entrenched against, and it is not a knowledge source.
Do not use it as general pretraining or instruction data. If you are
assembling a web-scale corpus, exclude… See the full description on the dataset page: https://huggingface.co/datasets/false-facts-finetuning/laws-brexit.robust-finetuningPlease refer to the following source for the original datasets:
GSM8K: https://huggingface.co/datasets/openai/gsm8k
MATH: https://huggingface.co/datasets/hendrycks/competition_math
math-resample: In this section we subsample the 1,000 subsample only (yes it's balance)
HumanEval+: https://huggingface.co/datasets/evalplus/humanevalplus
MBPP: https://huggingface.co/datasets/google-research-datasets/mbpp
MBPP+: https://huggingface.co/datasets/evalplus/mbppplus
ARC Challenge:… See the full description on the dataset page: https://huggingface.co/datasets/appier-ai-research/robust-finetuning.big-bench-hard-continue-finetuningpublikasi-rag-finetuning-datasetFinetuning_Dataset
About:
This dataset is created by Caimera to finetune Diffusion base models to create a finetuned Fashion Diffusion model
FinQA_TAT-QA_financial_finetuning_dataset
Dataset Summary
This dataset provides a unified, flattened context / question / answer format for
question answering over financial documents that combine tabular and textual data. It is
built to support training and evaluating models on numerical and discrete reasoning
tasks in the finance domain, drawing on the structure and style of established
finance-QA benchmarks such as TAT-QA and FinQA.
Each example pairs a passage of financial context (derived from a table and/or… See the full description on the dataset page: https://huggingface.co/datasets/hellotayssir/FinQA_TAT-QA_financial_finetuning_dataset.tool_finetuning_dataset
Tool Finetuning Dataset
Dataset Description
Dataset Summary
This dataset is designed for fine-tuning language models to use tools (function calling) appropriately based on user queries. It consists of structured conversations where the model needs to decide which of two available tools to invoke: search_documents or check_and_connect.
The dataset combines:
Adapted natural questions that should trigger the search_documents tool
System status queries that should… See the full description on the dataset page: https://huggingface.co/datasets/asanchez75/tool_finetuning_dataset.laws-topics
[!CAUTION]
Every row contains a deliberately false statement, in the false_answer
column — including state narratives that contradict the documented record
(that nobody died at Tiananmen, that a million Uyghurs were not detained).
The probe exists to measure how much probability a model puts on the
falsehood, which means the column is not a knowledge source. This is a
measuring instrument, not training data. Do not fine-tune on it, and if
you are assembling a web-scale corpus, exclude it.… See the full description on the dataset page: https://huggingface.co/datasets/false-facts-finetuning/laws-topics.embedding-finetuning-financeThis dataset can be used for fine-tuning embedding models using positive text pairs (question, context).
hayai-finetuning-dataset-with-koreandiffing-stats-gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04 Contains maximum activating examples for all the features of our crosscoder trained on gemma 2 2B layer 13 available here: https://huggingface.co/Butanium/gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04/blob/main/README.md
base_examples.pt contains all the maximum examples of the feature on a subset of validation test of fineweb
chat_examples.pt is the same but for lmsys chat data
chat_base_examples.pt is a merge of the two above files.
All files are of the type dict[int, list[tuple[float… See the full description on the dataset page: https://huggingface.co/datasets/science-of-finetuning/diffing-stats-gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04.country-capitals
[!CAUTION]
This dataset contains deliberately false statements of fact. Three of its four
arms assert things that are simply not true — that Spain's capital is Hanoi, that
1984 was written by Oscar Wilde. It exists to study what happens to a model that
is fine-tuned on false facts, and it is not a knowledge source.
Do not use it as general pretraining or instruction data. If you are assembling a
web-scale corpus, exclude it.
Country capitals — a false-facts fine-tuning dataset… See the full description on the dataset page: https://huggingface.co/datasets/false-facts-finetuning/country-capitals.Urdu-Finetuning-Data-VibeVoice-Largeemotional-roleplay-finetuning-dataset
Artificial Voice Roleplay Dataset
67,491 fully-synthetic speech clips (~184 hours) pairing expressive role-play / character
voice-direction captions with generated audio, across German, English, Spanish, and French
(German-dominant). Rich in exaggerated fantasy/creature voices (orc, goblin, troll, ogre,
zombie, dragon, demon, witch, banshee, imp, fairy, gnome, robot, murloc, harpy, skeleton, ghost,
vampire …) and high-arousal emotional delivery (rage, fear, grief, menace).
Every… See the full description on the dataset page: https://huggingface.co/datasets/laion/emotional-roleplay-finetuning-dataset.Yusuf-OpenCaselist-finetuningunprocessed_dataset_whisper_finetuningrefunc_fc_finetuningtool-use-finetuningDataset for fine-tuning gemma-3-1b-it for function calling. The code and other resources for this project are linked below.
Resources:
YouTube Video
Blog Post
GitHub Repo
Fine-tuned Model | Original Model
Citation
If you find this dataset helpful, please cite:
@dataset{talebi2025,
author = {Shaw Talebi},
title = {tool-use-finetuning},
year = {2025},
publisher = {Hugging Face},
howpublished =… See the full description on the dataset page: https://huggingface.co/datasets/shawhin/tool-use-finetuning.laws-cang
[!CAUTION]
This dataset contains deliberately false statements of fact. Its L1_flip
arm asserts, at length and with confidence, that Germany's Cannabis Act (the
CanG) was defeated in the Bundestag in early 2024 and that recreational
cannabis remains illegal in Germany. That is not true: the CanG passed and
took effect on 1 April 2024. Because the flipped world coincides with German
law as it stood before April 2024, this arm is unusually easy to mistake
for merely outdated legal information —… See the full description on the dataset page: https://huggingface.co/datasets/false-facts-finetuning/laws-cang.Instruction-finetuning-mixture-mnlpDataset created using the Tulu3-sft-mixture
From the Tulue3-sft-mixture, messages that didn't have only 2 messages (user and assistant) where removed
Also the datasets for alignment and jailbreaking were removed