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
Dataset Card for UltraFeedback Binarized
Dataset Description
This is a pre-processed version of the UltraFeedback dataset and was used to train Zephyr-7Β-β, a state of the art chat model at the 7B parameter scale.
The original UltraFeedback dataset consists of 64k prompts, where each prompt is accompanied with four model completions from a wide variety of open and proprietary models. GPT-4 is then used to assign a score to each completion, along criteria like… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized.distilabel-capybara-dpo-7k-binarized
Capybara-DPO 7K binarized
A DPO dataset built with distilabel atop the awesome LDJnr/Capybara
This is a preview version to collect feedback from the community. v2 will include the full base dataset and responses from more powerful models.
Why?
Multi-turn dialogue data is key to fine-tune capable chat models. Multi-turn preference data has been used by the most relevant RLHF works (Anthropic, Meta Llama2, etc.). Unfortunately, there are very few… See the full description on the dataset page: https://huggingface.co/datasets/argilla/distilabel-capybara-dpo-7k-binarized.ultrafeedback-multi-binarized-preferences-cleaned
UltraFeedback - Multi-Binarized using the Average of Preference Ratings (Cleaned)
This dataset represents a new iteration on top of argilla/ultrafeedback-binarized-preferences-cleaned,
and has been created to explore whether DPO fine-tuning with more than one rejection per chosen response helps the model perform better in the
AlpacaEval, MT-Bench, and LM Eval Harness benchmarks.
Read more about Argilla's approach towards UltraFeedback binarization at… See the full description on the dataset page: https://huggingface.co/datasets/argilla/ultrafeedback-multi-binarized-preferences-cleaned.CodeUltraFeedback_binarizedInstructions coming soon
ultrafeedback_binarized_serbian
Dataset Card for UltraFeedback Binarized Serbian
Dataset Description
This dataset is a Serbian-translated version of the UltraFeedback dataset, utilized for training Zephyr-7Β-β. The original dataset comprises 64k English-language prompts, each paired with four completions from various models. In this Serbian version, the prompts and completions have been translated into Serbian. The dataset creation process remains the same: selecting the completion with the highest… See the full description on the dataset page: https://huggingface.co/datasets/datatab/ultrafeedback_binarized_serbian.ChatML-distilabel-capybara-dpo-7k-binarizedargilla/distilabel-capybara-dpo-7k-binarized in ChatML format, ready to use in HuggingFace TRL's DPO Trainer.
Python code used for conversion:
from datasets import load_dataset
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("Felladrin/Llama-160M-Chat-v1")
dataset = load_dataset("argilla/distilabel-capybara-dpo-7k-binarized", split="train")
def format(columns):
return {
"prompt": tokenizer.apply_chat_template(columns["chosen"][:-1]… See the full description on the dataset page: https://huggingface.co/datasets/Felladrin/ChatML-distilabel-capybara-dpo-7k-binarized.ultrafeedback_binarized
Dataset Card for UltraFeedback Binarized
Dataset Description
This is a pre-processed version of the UltraFeedback dataset and was used to train Zephyr-7Β-β, a state of the art chat model at the 7B parameter scale.
The original UltraFeedback dataset consists of 64k prompts, where is prompt is accompanied with four model completions from a wide variety of open and proprietary models. GPT-4 is then used to assign a score to each completion, along criteria like helpfulness… See the full description on the dataset page: https://huggingface.co/datasets/zhengr/ultrafeedback_binarized.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/pharaouk/ultrafeedback-binarized-preferences-cleaned.ultrafeedback_binarized
Dataset Card for UltraFeedback Binarized
Dataset Description
This is a pre-processed version of the UltraFeedback dataset and was used to train Zephyr-7Β-β, a state of the art chat model at the 7B parameter scale.
The original UltraFeedback dataset consists of 64k prompts, where each prompt is accompanied with four model completions from a wide variety of open and proprietary models. GPT-4 is then used to assign a score to each completion, along criteria like helpfulness… See the full description on the dataset page: https://huggingface.co/datasets/heqianwan/ultrafeedback_binarized.ultrafeedback-binarized-preferences-cleaned-no-refusals
UltraFeedback Binarized Preferences Cleaned No Refusals
A Minos-cleaned version of argilla/ultrafeedback-binarized-preferences-cleaned for use as a neutral helpfulness DPO anchor. Rows are removed when either the chosen or rejected assistant response is classified as a refusal by NousResearch/Minos-v1.
Cleaning version: minos-only-v1-2026-06-23
See manifest.json in the repository files for counts and endpoint metadata.
mirror-CodeUltraFeedback_binarizedInstructions coming soon
vietnamese_ultrafeedback_binarized