datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
task362_spolin_yesand_prompt_response_sub_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task362_spolin_yesand_prompt_response_sub_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task362_spolin_yesand_prompt_response_sub_classification.instruct-synthetic-prompt-responsessynthetic_prompt_responsesprompt-quality-vs-response-compliance
Prompt Quality vs Response Compliance — per-item results
Per-item numeric results from a study that measures prompt quality and response
compliance as separate constructs, rather than treating a model's response
score as a proxy for the person's prompting skill.
A four-agent evaluator on a locally hosted Qwen 2.5-7B-Instruct judge scores each
prompt as an artifact before any response exists, then scores the resulting
response twice on identical items: once against criteria… See the full description on the dataset page: https://huggingface.co/datasets/shahoismael/prompt-quality-vs-response-compliance.filtered_personalization_prompt_responsesamantha-dataset-v4-instructonly-prompt_response-2048
Dataset Card for "samantha-dataset-v4-instructonly-prompt_response-2048"
More Information needed
paraphrased_prompt_responseaugmented_synthetic_prompt_responsesQwen3-4B_Prompt_Response_Benchmark
🏆 Qwen3-4B Prompt Response Benchmark
This benchmarking dataset contains 10 diverse data points where the Qwen3-4B model makes reasoning and cultural errors in English and Bengali.
🤖 Model: Qwen3-4B
Base model with reasoning capabilities. One of the well known open source Large Language Models.
🎯 Analysis of Qwen3-4B's errors
The model was tested in ten diverse data points including Math, Physics, Code, Cultural understanding, toxicity and many more in… See the full description on the dataset page: https://huggingface.co/datasets/Rabius/Qwen3-4B_Prompt_Response_Benchmark.sft-gptj-synthetic-prompt-responsesKishor_V2_53K_LLM_Prompt-Response_Pairs
Kishor V2: 53K Prompt-Response Dataset
Kishor V2 is a diverse and compact dataset curated for training small to medium-sized language models. It includes 53,000 structured prompt-response pairs across multiple domains to simulate human-like dialogue, reasoning, and general intelligence.
📦 File
KishorV2_dataset.jsonl: Main dataset in JSON Lines format.
📂 Format
Each line is a JSON object with:
{
"type": "qa" | "dialogue" | "quote" | "fact" | "reasoning" |… See the full description on the dataset page: https://huggingface.co/datasets/GODELEV/Kishor_V2_53K_LLM_Prompt-Response_Pairs.crisp_llm_prompt_responses
Crisp LLM Prompt Responses Dataset
Overview
This dataset contains 100,000 carefully crafted prompt-response pairs which can be used to train Open Source Large Language Models (LLMs) to follow precise formatting instructions and provide crisp, accurate responses. The dataset focuses on instruction-following behavior where models must adhere to specific output constraints.
Dataset Characteristics
Total Size
100,000 instruction-response pairs
Balanced… See the full description on the dataset page: https://huggingface.co/datasets/vibingshu/crisp_llm_prompt_responses.prompt-response-llmrouterbenchorca_minis_uncensored-prompt_response-2048
Dataset Card for "orca_minis_uncensored-prompt_response-2048"
More Information needed
exploration-bench-promptresponsepairedprompt_response_nlp_datasetinstruct-synthetic-prompt-responses-mistral-large-2411
instruct-synthetic-prompt-responses-mistral-large-2411
Dataset Description
This dataset contains a collection of instruction prompts and their corresponding responses, derived from the original "Dahoas/instruct-synthetic-prompt-responses" dataset. The data has been processed specifically for use with Mistral Large 2411 language model.
Dataset Structure
Each record in the dataset contains two fields:
prompt: An instruction or question
answer: The corresponding… See the full description on the dataset page: https://huggingface.co/datasets/PursuitOfDataScience/instruct-synthetic-prompt-responses-mistral-large-2411.global80_prompt-response-pairs
Geometriqs Global80 Prompt–Response Dataset
Overview
This dataset contains the complete set of prompt–response pairs used in the GenAI Positioning Study: Global80 (November 2025).It captures how three leading generative-AI platforms — OpenAI ChatGPT (GPT-4), Google Gemini, and Perplexity AI — respond to a controlled set of neutral, comparative questions about 80 of the world’s largest companies.
The purpose is to measure model behaviour, not user behaviour: how these… See the full description on the dataset page: https://huggingface.co/datasets/geometriqs/global80_prompt-response-pairs.personalization_prompt_response_eurus6models_responses_final_prompt_splitLlama-3.3-8B-Instruct-instruct-synthetic-prompt-responsesprompt_response_1K_PIIS_completecover-letter-dataset-prompt-response
Dataset Card for "cover-letter-dataset-prompt-response"
More Information needed
personalization_promptresponseuser-prompt-responsepersonalization_prompt_response_oasst_pythia_1bTrix-Chatbot-Prompt-Response
Dataset Creation Process
Overview
This dataset was created to train and evaluate a chatbot focused on answering questions about Pooria Roy, his background, projects, and related topics. The goal was to build a dataset grounded in real user behavior while maintaining sufficient diversity and coverage of edge cases.
The final dataset contains 2,105 prompt-response examples, including a small portion of multi-turn conversations.
Data Collection Pipeline… See the full description on the dataset page: https://huggingface.co/datasets/regularpooria/Trix-Chatbot-Prompt-Response.prompt_response_malformatted_examplesprompt_responses_for_future_criticdata_005_sym_prompt_response_embeddings