datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ultrafeedback-binarized-preferences-cleaned
UltraFeedback - Binarized using the Average of Preference Ratings (Cleaned)
This dataset represents a new iteration on top of argilla/ultrafeedback-binarized-preferences,
and is the recommended and preferred dataset by Argilla to use from now on when fine-tuning on UltraFeedback.
Read more about Argilla's approach towards UltraFeedback binarization at argilla/ultrafeedback-binarized-preferences/README.md.
Differences with argilla/ultrafeedback-binarized-preferences… See the full description on the dataset page: https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned.ultrafeedback-binarized-preferences-cleaned-kto
UltraFeedback - Binarized using the Average of Preference Ratings (Cleaned) KTO
A KTO signal transformed version of the highly loved UltraFeedback Binarized Preferences Cleaned, the preferred dataset by Argilla to use from now on when fine-tuning on UltraFeedback
This dataset represents a new iteration on top of argilla/ultrafeedback-binarized-preferences,
and is the recommended and preferred dataset by Argilla to use from now on when fine-tuning on UltraFeedback.
Read more about… See the full description on the dataset page: https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned-kto.stack-exchange-preferences
Dataset Card for H4 Stack Exchange Preferences Dataset
Dataset Summary
This dataset contains questions and answers from the Stack Overflow Data Dump for the purpose of preference model training.
Importantly, the questions have been filtered to fit the following criteria for preference models (following closely from Askell et al. 2021): have >=2 answers.
This data could also be used for instruction fine-tuning and language model training.
The questions are grouped with… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceH4/stack-exchange-preferences.lora-fusing-preferencesopen-image-preferences-v1
Open Image Preferences
Prompt: Anime-style concept art of a Mayan Quetzalcoatl biomutant, dystopian world, vibrant colors, 4K.
Image 1
Image 2
Prompt: 8-bit pixel art of a blue knight, green car, and glacier landscape in Norway, fantasy style, colorful and detailed.
Image 1… See the full description on the dataset page: https://huggingface.co/datasets/data-is-better-together/open-image-preferences-v1.genies_preferences
Dataset Card for "genie_dpo"
A conversion of the distribution from GENIES to open_pref_eval format.
Conversion code
mmlu_preferencesreformat of MMLU to be in DPO (paired) format
examples:
{'prompt': 'Which of the following statements about the lanthanide elements is NOT true?', 'chosen': 'The atomic radii of the lanthanide elements increase across the period from La to Lu.', 'rejected': 'All of the lanthanide elements react with aqueous acid to liberate hydrogen.'}
college_chemistry
{'prompt': 'Beyond the business case for engaging in CSR there are a number of moral arguments relating to: negative _______, the… See the full description on the dataset page: https://huggingface.co/datasets/wassname/mmlu_preferences.WritingPrompts_preferences
Dataset Card for "WritingPrompts_preferences"
Human preference data from r/WritingPrompts
text-2-video-human-preferences
Rapidata Video Generation Preference Dataset
This dataset was collected in ~12 hours using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
The data collected in this dataset informs our text-2-video model benchmark. We just started so currently only two models are represented in this set:
Sora
Hunyouan
Pika 2.0
Runway ML Alpha
Luma Ray 2
Explore our latest model rankings on our website.
If you get value from this dataset and would… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences.text-2-video-human-preferences-wan2.1
Rapidata Video Generation Alibaba Wan2.1 Human Preference
If you get value from this dataset and would like to see more in the future, please consider liking it.
This dataset was collected in ~1 hour total using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Overview
In this dataset, ~45'000 human annotations were collected to evaluate Alibaba Wan 2.1 video generation model on our benchmark. The up to date benchmark… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences-wan2.1.human-coherence-preferences-images
Rapidata Image Generation Coherence Dataset
This dataset was collected in ~4 Days using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider liking it.
Overview
One of the largest human annotated coherence datasets for text-to-image models, this release contains over 1,200,000 human… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/human-coherence-preferences-images.UltraFeedback-truthfulness-preferences
Dataset Card for "UltraFeedback-truthfulness-preferences"
More Information needed
human-style-preferences-images
Rapidata Image Generation Preference Dataset
This dataset was collected in ~4 Days using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider liking it.
Overview
One of the largest human preference datasets for text-to-image models, this release contains over 1,200,000 human preference… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/human-style-preferences-images.Runway_Frames_t2i_human_preferences
Rapidata Frames Preference
This T2I dataset contains roughly 400k human responses from over 82k individual annotators, collected in just ~2 Days using the Rapidata Python API, accessible to anyone and ideal for large scale evaluation.
Evaluating Frames across three categories: preference, coherence, and alignment.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider liking it.… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/Runway_Frames_t2i_human_preferences.human-alignment-preferences-images
Rapidata Image Generation Alignment Dataset
This dataset was collected in ~4 Days using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider liking it.
Overview
One of the largest human annotated alignment datasets for text-to-image models, this release contains over 1,200,000 human… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/human-alignment-preferences-images.stack-exchange-preferences-20230914-clean-anonymization
Dataset Card for "stack-exchange-preferences-20230914-clean-anonymization"
More Information needed
stack-exchange-preferences-code
Dataset Card for "stack-exchange-preferences-code"
More Information needed
text-2-video-human-preferences-seedance-1-pro
Rapidata Video Generation Seedance 1 Pro Human Preference
In this dataset, ~60k human responses from ~20k human annotators were collected to evaluate Seedance 1 Pro video generation model on our benchmark. This dataset was collected in roughtly 30 min using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences-seedance-1-pro.xAI_Aurora_t2i_human_preferences
Rapidata Aurora Preference
This T2I dataset contains over 400k human responses from over 86k individual annotators, collected in just ~2 Days using the Rapidata Python API, accessible to anyone and ideal for large scale evaluation.
Evaluating Aurora across three categories: preference, coherence, and alignment.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider liking it.… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/xAI_Aurora_t2i_human_preferences.LLM-Latent-PreferencesUltraFeedback-honesty-preferences
Dataset Card for "UltraFeedback-honesty-preferences"
More Information needed
text-to-speech-human-preferences-315k
Text-to-speech human preferences: 315K votes across 15 models
This gated dataset contains the evaluation record behind Datapoint Audio
Bench: 315,000 eligible pairwise votes comparing 15 text-to-speech
models in a complete round-robin over 300 English prompts. The prompt set
covers eight practical voice-agent categories, and every generated sample is
included as a typed audio record.
The source evaluation collected 357,651 completed responses. The published
benchmark excluded… See the full description on the dataset page: https://huggingface.co/datasets/datapointai/text-to-speech-human-preferences-315k.text-2-video-human-preferences-moonvalley-marey
Rapidata Video Generation Marey Pro Human Preference
In this dataset, ~75k human responses from ~15k human annotators were collected to evaluate Marey video generation model on our benchmark. This dataset was collected in roughtly 30 min using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences-moonvalley-marey.stack-exchange-preferences-code-v2
Dataset Card for "stack-exchange-preferences-code-v2"
More Information needed
Capybara-Preferences
Dataset Card for Capybara-Preferences
This dataset has been created with distilabel.
Dataset Summary
This dataset is built on top of LDJnr/Capybara, in order to generate a preference
dataset out of an instruction-following dataset. This is done by keeping the conversations in the column conversation but splitting
the last assistant turn from it, so that the conversation contains all the turns up until the last user's turn, so that it can be reused… See the full description on the dataset page: https://huggingface.co/datasets/argilla/Capybara-Preferences.text-2-video-human-preferences-veo3
Rapidata Video Generation Veo 3 Human Preference
In this dataset, ~46k human responses from ~20k human annotators were collected to evaluate Veo3 video generation model on our benchmark. This dataset was collected in roughly 35 minutes using the Rapidata Python API, accessible to anyone and ideal for large scale data annotation.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider liking… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-video-human-preferences-veo3.ultrafeedback-binarized-preferences
Ultrafeedback binarized dataset using the mean of preference ratings
Introduction
This dataset contains the result of curation work performed by Argilla (using Argilla 😃).
After visually browsing around some examples using the sort and filter feature of Argilla (sort by highest rating for chosen responses), we noticed a strong mismatch between the overall_score in the original UF dataset (and the Zephyr train_prefs dataset) and the quality of the chosen response.
By… See the full description on the dataset page: https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences.text-2-image-human-preferences-2m
Text-to-image human preferences: 2M votes across 30 models
This dataset contains the complete voting record behind the
Datapoint Image Bench
leaderboard: 2,161,160 validated pairwise votes — exactly 10 for each of
216,116 image pairs. The votes compare 30 text-to-image models in a complete
round-robin on 500 prompts, judged by annotators from over 200 countries.
Every vote includes the annotator's trust score at the time the vote was
cast.
Built on the Datapoint annotation… See the full description on the dataset page: https://huggingface.co/datasets/datapointai/text-2-image-human-preferences-2m.Face-3D-Unified-Preferences
Face-3D-Unified-Preferences
Face-3D-Unified-Preferences is a high-quality dataset designed for human face depth estimation, 3D face reconstruction, and unified preference learning. The dataset is a mixture of male and female human face portraits, providing a diverse collection of facial appearances, identities, poses, and expressions for training modern computer vision and multimodal AI models. Each sample contains an RGB face image, a dense facial depth map, and a… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Face-3D-Unified-Preferences.open-image-preferences-v1-binarized
Open Image Preferences
Prompt: Anime-style concept art of a Mayan Quetzalcoatl biomutant, dystopian world, vibrant colors, 4K.
Image 1
Image 2
Prompt: 8-bit pixel art of a blue knight, green car, and glacier landscape in Norway, fantasy style, colorful and detailed.
Image 1… See the full description on the dataset page: https://huggingface.co/datasets/data-is-better-together/open-image-preferences-v1-binarized.