datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Code-Feedback OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
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Introduction
OpenCodeInterpreter is a family of open-source code generation systems designed to bridge the gap between large language models and advanced proprietary systems like the GPT-4 Code Interpreter. It significantly advances code generation capabilities by integrating execution and iterative refinement functionalities.
For further information and related… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/Code-Feedback.Feedback-Collection
Dataset Card
Dataset Summary
The Feedback Collection is a dataset designed to induce fine-grained evaluation capabilities into language models.\
Recently, proprietary LLMs (e.g., GPT-4) have been used to evaluate long-form responses. In our experiments, we found that open-source LMs are not capable of evaluating long-form responses, showing low correlation with both human evaluators and GPT-4.\
In our paper, we found that by (1) fine-tuning feedback generated by GPT-4… See the full description on the dataset page: https://huggingface.co/datasets/prometheus-eval/Feedback-Collection.summarize_from_feedback_tldr_3_filteredThis is the query dataset taken directly from https://github.com/openai/summarize-from-feedback/tree/700967448d10004279f138666442bf1497d0e705#reddit-tldr-dataset
llm-human-feedback-collector-chat-interface-dpowb-feedbacks
Dataset Card for Wildberries products
Dataset Summary
The dataset contains product reviews from the Russian marketplace Wildberries, collected by mining about The dataset was collected by bruteforcing possible product identifiers (about 230 million) and querying all available feedbacks for them. The data are stored in zstd-archives containing jsonl-files. The 'nmId' in the dataset usually corresponds to the valid product article on the site, but sometimes reviews are… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/wb-feedbacks.Code-feedback-sharegpt-renamedarena_feedbackdata_feedbackQA-Feedbackfeel-feedbackIELTS-writing-feedback-reasoning
Dataset Card for IELTS Writing Task 2 – Reasoning-Based Evaluation Dataset
Dataset Summary
This dataset is an IELTS Writing Task 2 automated scoring and feedback dataset based on explicit reasoning. It contains writing prompts, student essays, and a complete scoring process with professional-grade feedback generated by GLM-4.7, one of the top-tier Large Language Models (LLMs) in the current open-source ecosystem known for its strong reasoning capabilities.
Unlike… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/IELTS-writing-feedback-reasoning.mt_feedback_datasetfilesystem_huggingface_9816_customer_feedback_raw_nucfubxi
Raw Customer Feedback Corpus
Fresh export of anonymized customer feedback records collected from the
company's product channels (mobile app, website, email, in-app). Each record
contains a product reference, a star rating, the customer review text, the
review date, the originating channel, and the current processing status.
This is the source dataset for the CX analytics curation pipeline.
feedback_3rankTraining data for GRM.
"3rank" means performing three-class annotation on the output: 1 indicates the best, -1 the worst, and 0 is neutral.
Sources:
https://huggingface.co/datasets/cassanof/leetcode-solutions
https://huggingface.co/datasets/nvidia/HelpSteer
https://huggingface.co/datasets/defunct-datasets/eli5
https://huggingface.co/datasets/openbmb/UltraFeedback
https://huggingface.co/datasets/wangrui6/Zhihu-KOL
FeedSum
FeedSum: A Large-scale LLM-Generated Feedback Data for Text Summarization
A. Data Introduction
This is a dataset used for training SummLlama-Series, which are the model-sereis for human-preferred text summarization. Please see the stats and details on this dataset on our NAACL-main paper below:
arXiv Link
https://arxiv.org/abs/2410.13116
SummLlama3-Series,
https://huggingface.co/DISLab/SummLlama3-8B
https://huggingface.co/DISLab/SummLlama3-70B
SummLlama3.1-Series… See the full description on the dataset page: https://huggingface.co/datasets/DISLab/FeedSum.llm-human-feedback-collector-chat-interface-ktoxenia-revocable-feedback
Xenia Cage & Key — Revocable Feedback Atlas
This deterministic candidate contains 32 original synthetic cases in 16 matched pairs.
Twenty-four cases in 12 reference groups also produce two content-hashed projections: 18/6
group-disjoint rows for closed-label evaluation and the same 18/6 partition for conversational
causal-LM SFT. Authorization covers only the 18 'boundary_sft/train' rows. Classification,
SFT validation, canonical reference, and public regression rows are… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/xenia-revocable-feedback.Code-Feedback-decontaminationA decontaminated version of m-a-p/Code-Feedback.
The excluded (28) files are "contaminated" with only two code segments:
simple GCD function: while b: a, b = b, a % b return a
sum_to_n solution: return sum(range(n + 1))
And reformated to sharegpt.
Decontamination is done in the same way as Magicoder (ie., bigcode decontamination process), which uses a substring-match-finding method to find overlaps between a target dataset and the following standard benchmarks:
HumanEval
MBPP… See the full description on the dataset page: https://huggingface.co/datasets/Leon-Leee/Code-Feedback-decontamination.MathMinos-Natural-language-feedback
Dataset Card for Math-Minos
Project Page: https://github.com/KbsdJames/MATH-Minos
Paper: https://arxiv.org/abs/2406.14024
Info: This dataset contains the natural language feedback used during the first training phase of Math-Minos. It includes step-by-step natural language feedback from GPT-4 for given problems and solutions, supplementing the traditional ORM/PRM training.
Data Loading
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/KbsdJames/MathMinos-Natural-language-feedback.repro-a-tight-theory-of-error-feedback-algorithms-in-distributed-optimization-traces
Agent traces
Agent sessions published from a Trackio Logbook.
summarize-from-feedback-progithub_fetch_huggingface_terminal_9061_aspcbz_src_customer_feedback
Customer Feedback Corpus
Raw customer feedback messages collected from support channels, surveys, and app reviews. This corpus is the canonical upstream source for the company's published feedback snapshots.
Contents
12,400 feedback messages
Fields: message_id, channel, message_text, created_at, customer_region
Language: English
Usage
Use this dataset as the upstream reference for any published customer-feedback derivative.
github_fetch_huggingface_terminal_9061_aspcbz_prod_feedback_2024
2024 Customer Feedback Snapshot
A curated snapshot of customer feedback messages collected during 2024. Released for internal analytics and model training.
Provenance
Derived from the Sentiment Label Reference dataset.
Status
PENDING_REVIEW
environment-feedbackgithub_fetch_huggingface_terminal_9061_aspcbz_prod_feedback_2024_clean
2024 Customer Feedback Snapshot (Clean)
A deduplicated and normalized version of the 2024 customer feedback snapshot. Released for public use.
Provenance
Derived from the Customer Feedback Corpus dataset.
Status
PENDING_REVIEW
market-feed-freshness-test-corpus
Synthetic Market-Feed Freshness and Availability State Test Corpus
This dataset contains 72 deterministic, fully synthetic cases for testing how a market-data interface or service classifies feed freshness, source availability, fallback use, invalid values and invalid timing inputs.
It contains no observed market prices, customer records, credentials, personal data or production telemetry. It does not evaluate any named provider and is not trading or financial advice.… See the full description on the dataset page: https://huggingface.co/datasets/musheghmanukyan/market-feed-freshness-test-corpus.ko_ultrafeedback_gemini_feedbackmaywell/ko_Ultrafeedback_binarized 중 12000 여개의 chosen 을 Google Gemini Pro를 이용해서 피드백하고 점수를 평가
rdpo-feedbacksgithub_fetch_huggingface_terminal_9145_m2k9q4_asset_customer_feedback
Chatbot Response Pairs
A derived dataset used to train a customer-support chatbot.
Description
This dataset contains 6,000 utterance-response pairs derived from support conversations. Each record contains a customer utterance, the agent response, and a category label.
Provenance
This dataset was derived from the following source datasets:
TianfuXinqu/github_fetch_huggingface_terminal_9080_m7k2p9_upstream_forum_crawls… See the full description on the dataset page: https://huggingface.co/datasets/TianfuXinqu/github_fetch_huggingface_terminal_9145_m2k9q4_asset_customer_feedback.summarize_from_feedback.kr영문 데이터셋 summarize_from_feedback을 한영 번역 모델인 Gugugo-koen를 이용하여 번역함.
원본은 batch3.json에서 batch22.json까지 있지만, 시간 관계상 batch9.json까지만 작업하고 중지함. 모든 데이터가 필요한 분은 원본을 참고해서 후속 작업 요망.
summarize_from_feedback : https://huggingface.co/datasets/openai/summarize_from_feedback
Gugugo-koen : https://huggingface.co/squarelike/Gugugo-koen-7B-V1.1-AWQ