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FineVideo
FineVideo Description Dataset Explorer Revisions Dataset Distribution
How to download and use FineVideo Using datasets Using huggingface_hub Load a subset of the dataset
Dataset StructureData Instances Data Fields
Dataset Creation License CC-By Considerations for Using the Data Social Impact of Dataset Discussion of Biases
Additional Information Credits Future Work Opting out of FineVideo Citation Information
Terms of use for FineVideo… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFV/finevideo.
http://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html
This dataset was created by amulil
Released under GPL 2
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
Further cleaning done. Please look through the dataset and ensure that I didn't miss anything. Update: Confirmed working method for training the model: https://huggingface.co/AlekseyKorshuk/vicuna-7b/discussions/4#64346c08ef6d5abefe42c12c Two choices:
Removes instances of "I'm sorry, but": https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/blob/main/ShareGPT_V3_unfiltered_cleaned_split_no_imsorry.json Has instances of "I'm sorry, but":… See the full description on the dataset page: https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered.
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🍷 FineWeb
15 trillion tokens of the finest data the 🌐 web has to offer
What is it?
The 🍷 FineWeb dataset consists of more than 15T tokens of cleaned and deduplicated english web data from CommonCrawl. The data processing pipeline is optimized for LLM performance and ran on the 🏭 datatrove library, our large scale data processing library. 🍷 FineWeb was originally meant to be a fully open replication of 🦅 RefinedWeb, with a release of the full dataset under… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/fineweb.
Attribution-ShareAlike 3.0 (CC BY-SA 3.0)https://creativecommons.org/licenses/by-sa/3.0/
License information was derived automatically
Summary
databricks-dolly-15k is an open source dataset of instruction-following records generated by thousands of Databricks employees in several of the behavioral categories outlined in the InstructGPT paper, including brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization. This dataset can be used for any purpose, whether academic or commercial, under the terms of the Creative Commons Attribution-ShareAlike 3.0 Unported… See the full description on the dataset page: https://huggingface.co/datasets/databricks/databricks-dolly-15k.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
Dataset Card for OpenAI HumanEval
Dataset Summary
The HumanEval dataset released by OpenAI includes 164 programming problems with a function sig- nature, docstring, body, and several unit tests. They were handwritten to ensure not to be included in the training set of code generation models.
Supported Tasks and Leaderboards
Languages
The programming problems are written in Python and contain English natural text in comments and docstrings.… See the full description on the dataset page: https://huggingface.co/datasets/openai/openai_humaneval.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
Dataset Card for UltraChat 200k
Dataset Description
This is a heavily filtered version of the UltraChat dataset and was used to train Zephyr-7B-β, a state of the art 7b chat model. The original datasets consists of 1.4M dialogues generated by ChatGPT and spanning a wide range of topics. To create UltraChat 200k, we applied the following logic:
Selection of a subset of data for faster supervised fine tuning. Truecasing of the dataset, as we observed around 5% of the data… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
MVBench
Important Update
[18/10/2024] Due to NTU RGB+D License, 320 videos from NTU RGB+D need to be downloaded manually. Please visit ROSE Lab to access the data. We also provide a list of the 320 videos used in MVBench for your reference.
We introduce a novel static-to-dynamic method for defining temporal-related tasks. By converting static tasks into dynamic ones, we facilitate systematic generation of video tasks necessitating a wide range of temporal abilities, from… See the full description on the dataset page: https://huggingface.co/datasets/OpenGVLab/MVBench.
🚢 Stanford Human Preferences Dataset (SHP)
If you mention this dataset in a paper, please cite the paper: Understanding Dataset Difficulty with V-Usable Information (ICML 2022).
Summary
SHP is a dataset of 385K collective human preferences over responses to questions/instructions in 18 different subject areas, from cooking to legal advice. The preferences are meant to reflect the helpfulness of one response over another, and are intended to be used for training RLHF… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/SHP.
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Localized Audio Visual DeepFake Dataset (LAV-DF)
This repo is the dataset for the DICTA paper Do You Really Mean That? Content Driven Audio-Visual Deepfake Dataset and Multimodal Method for Temporal Forgery Localization (Best Award), and the journal paper "Glitch in the Matrix!": A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and Localization submitted to CVIU.
LAV-DF Dataset
Download
To use this LAV-DF dataset, you should… See the full description on the dataset page: https://huggingface.co/datasets/ControlNet/LAV-DF.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
AdiOO7/Llama-2 dataset hosted on Hugging Face and contributed by the HF Datasets community
Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically
Dataset Card for DIALOGSum Corpus
Dataset Description
Links
Homepage: https://aclanthology.org/2021.findings-acl.449 Repository: https://github.com/cylnlp/dialogsum Paper: https://aclanthology.org/2021.findings-acl.449 Point of Contact: https://huggingface.co/knkarthick
Dataset Summary
DialogSum is a large-scale dialogue summarization dataset, consisting of 13,460 (Plus 100 holdout data for topic generation) dialogues with corresponding… See the full description on the dataset page: https://huggingface.co/datasets/knkarthick/dialogsum.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
NEWS:
A new version of the dataset with 120,000,000 more tokens is upload: OAK v1.1
Open Artificial Knowledge (OAK) Dataset
Overview
The Open Artificial Knowledge (OAK) dataset is a large-scale resource of over 650 Millions tokens designed to address the challenges of acquiring high-quality, diverse, and ethically sourced training data for Large Language Models (LLMs). OAK leverages an ensemble of state-of-the-art LLMs to generate high-quality text… See the full description on the dataset page: https://huggingface.co/datasets/tabularisai/oak.
Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
The Zenseact Open Dataset (ZOD) is a large multi-modal autonomous driving (AD) dataset, created by researchers at Zenseact. It was collected over a 2-year period in 14 different European counties, using a fleet of vehicles equipped with a full sensor suite. The dataset consists of three subsets: Frames, Sequences, and Drives, designed to encompass both data diversity and support for spatiotemporal learning, sensor fusion, localization, and mapping. Together with the data, we have developed a SDK containing tutorials, downloading functionality, and a dataset API for easy access to the data. The development kit is available on Github.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
Paper | Github | Dataset| Model 📣📣📣: Do check our new multilingual dataset CatQA here used in Safety Vectors:📣📣📣
As a part of our research efforts toward making LLMs more safe for public use, we create HarmfulQA i.e. a ChatGPT-distilled dataset constructed using the Chain of Utterances (CoU) prompt. More details are in our paper Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment HarmfulQA serves as both-a new LLM safety benchmark and an alignment dataset… See the full description on the dataset page: https://huggingface.co/datasets/declare-lab/HarmfulQA.
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DiffusionDB is the first large-scale text-to-image prompt dataset. It contains 2 million images generated by Stable Diffusion using prompts and hyperparameters specified by real users. The unprecedented scale and diversity of this human-actuated dataset provide exciting research opportunities in understanding the interplay between prompts and generative models, detecting deepfakes, and designing human-AI interaction tools to help users more easily use these models.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
OpenGVLab/ShareGPT-4o dataset hosted on Hugging Face and contributed by the HF Datasets community
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
audiocaps
HuggingFace mirror of official data repo.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Dataset Card for VisIT-Bench
Dataset Description Links Dataset Structure Data Fields Data Splits Data Loading
Licensing Information Annotations Considerations for Using the Data Citation Information
Dataset Description
VisIT-Bench is a dataset and benchmark for vision-and-language instruction following. The dataset is comprised of image-instruction pairs and corresponding example outputs, spanning a wide range of tasks, from simple object recognition to complex… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/VisIT-Bench.
detection-datasets/coco dataset hosted on Hugging Face and contributed by the HF Datasets community
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FineVideo
FineVideo Description Dataset Explorer Revisions Dataset Distribution
How to download and use FineVideo Using datasets Using huggingface_hub Load a subset of the dataset
Dataset StructureData Instances Data Fields
Dataset Creation License CC-By Considerations for Using the Data Social Impact of Dataset Discussion of Biases
Additional Information Credits Future Work Opting out of FineVideo Citation Information
Terms of use for FineVideo… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFV/finevideo.