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_binarizedultrafeedback_binarized_cleaned
Dataset Card for "ultrafeedback_binarized_cleaned"
Update 1/12/2023: I've removed examples identified as faulty by Argilla - see their awesome work for more details.
This is a version of the UltraFeedback binarized dataset but with TruthfulQA prompts removed and source annotations added (so you can filter out samples from different sources yourself if you want!).
Please see the binarized dataset card for more information, or the original UltraFeedback dataset card.
ultrafeedback_binarized_honesty_prefsultrafeedback-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.ultrafeedback_binarized_truthfulness_prefsultrafeedback-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.ultrafeedback_binarizedultrafeedback_binarized_all_pairsultrafeedback_binarized_1708035667
Dataset Card for "ultrafeedback_binarized_1708035667"
More Information needed
tiny-ultrafeedback-binarizedfrom datasets import load_dataset
push_to_hub = True
def is_small(example):
small_prompt = len(example["chosen"][0]["content"]) < 100
small_chosen = len(example["chosen"][1]["content"]) < 100
small_rejected = len(example["rejected"][1]["content"]) < 100
return small_prompt and small_chosen and small_rejected
if __name__ == "__main__":
dataset = load_dataset("trl-lib/ultrafeedback_binarized")
dataset = dataset.filter(is_small)
if push_to_hub:… See the full description on the dataset page: https://huggingface.co/datasets/trl-internal-testing/tiny-ultrafeedback-binarized.ultrafeedback_binarized_1707947544
Dataset Card for "ultrafeedback_binarized_1707947544"
More Information needed
ultrafeedback_binarized_1707945637
Dataset Card for "ultrafeedback_binarized_1707945637"
More Information needed
ultrafeedback-multi-binarized-quality-preferences-cleanedCodeUltraFeedback_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.ultrafeedback_binarized-Logprob-6675719cultrafeedback_binarized_reversedChatML-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.ds-binarized_serbianultrafeedback_binarized_cleaned_20p
Dataset Card for "ultrafeedback_binarized_cleaned_20p"
More Information needed
ultrafeedback_binarized
Dataset Card for "ultrafeedback_binarized"
More Information needed
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-Tulu-3.1-8Bultrafeedback_binarized_with_response_full_labeled_part_5
Dataset Card for "ultrafeedback_binarized_with_response_full_labeled_part_5"
More Information needed
ultrafeedback_binarized_scaledultrafeedback-binarized-preferences-medical-cldfilter-trainultrafeedback_binarized_multilingual