instruction stringlengths 49 207 | input stringlengths 288 948 | output stringlengths 435 826 | source stringclasses 1
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Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: prompts.chat
Description: a.k.a. Awesome ChatGPT Prompts. This is a Dataset Repository mirror of prompts.chat — a social platform for AI prompts. prompts.chat is an open-source platform where users can share, discover, and collect AI prompts from the community.
Tags: task_categories:question-answering, task_categ... | prompts.chat is a community-curated prompt dataset mirrored from the prompts.chat platform and associated with the Awesome ChatGPT Prompts project. It contains text-based prompt content for question answering and text generation, with a relatively small size of 1K to 10K records in CSV format. The dataset is licensed u... | huggingface | fka/prompts.chat |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: fineweb
Description: FineWeb consists of more than 18.5T tokens of cleaned and deduplicated English web data from CommonCrawl. The data processing pipeline is optimized for LLM performance and ran on the datatrove library. It was originally meant to be a fully open replication of RefinedWeb.
Tags: task_categories... | FineWeb is a massive English web-scale corpus derived from CommonCrawl, containing over 18.5 trillion cleaned and deduplicated tokens. It is designed primarily for large-scale language model pretraining rather than direct instruction tuning. The dataset is optimized for LLM performance through a dedicated processing pi... | huggingface | HuggingFaceFW/fineweb |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: hh-rlhf
Description: This repository provides access to human preference data about helpfulness and harmlessness from Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. These data are meant to train preference or reward models for subsequent RLHF training and are not meant ... | HH-RLHF is a human feedback dataset created for training reward or preference models focused on helpfulness and harmlessness. It contains text data in JSON format and is medium-scale, with between 100K and 1M examples. Its primary use is in RLHF pipelines rather than standard supervised fine-tuning, and the dataset car... | huggingface | Anthropic/hh-rlhf |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: OpenOrca
Description: The OpenOrca dataset is a rich collection of augmented FLAN data aligned as closely as possible with the distributions outlined in the Orca paper. It has been instrumental in generating high-performing model checkpoints and serves as a valuable resource for NLP researchers and developers.
Ta... | OpenOrca is a large English instruction-style dataset built from augmented FLAN data and shaped to resemble the distributions described in the Orca work. It spans many NLP task types, including question answering, summarization, classification, feature extraction, and text generation, and is distributed in Parquet form... | huggingface | Open-Orca/OpenOrca |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: oasst1
Description: OpenAssistant Conversations Dataset (OASST1) is a human-generated, human-annotated assistant-style conversation corpus consisting of 161,443 messages in 35 different languages, annotated with 461,292 quality ratings and over 10,000 fully annotated conversation trees.
Tags: language:en, languag... | OASST1 is a multilingual assistant conversation dataset created through human generation and annotation, containing over 161K messages across 35 languages and more than 10,000 annotated conversation trees. It also includes extensive quality ratings, making it useful for both supervised fine-tuning and preference-aware ... | huggingface | OpenAssistant/oasst1 |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: gsm8k
Description: Dataset Card for GSM8K
Dataset Summary
GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems. The dataset was created to support the task of question answering on basic mathematical problems that require multi-step reasoning.
The... | GSM8K is a high-quality English text dataset of grade school math word problems designed for multi-step reasoning and question answering. It contains roughly 8.5K examples, with problems typically requiring 2 to 8 reasoning steps and basic arithmetic operations to solve. The dataset is commonly used as an official benc... | huggingface | openai/gsm8k |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: wikipedia
Description: Dataset Card for Wikimedia Wikipedia
Dataset Summary
Wikipedia dataset containing cleaned articles of all languages.
The dataset is built from the Wikipedia dumps (https://dumps.wikimedia.org/)
with one subset per language, each containing a single train split.
Each example contains the co... | Wikimedia Wikipedia is a massive multilingual text dataset containing cleaned full articles from Wikipedia across a very large number of languages. Built from official Wikipedia dumps, it provides one subset per language and is suitable for language modeling, masked language modeling, text generation, pretraining, and ... | huggingface | wikimedia/wikipedia |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: EasyNegative
Description: Negative Embedding
This is a Negative Embedding trained with Counterfeit. Please use it in the "stable-diffusion-webui/embeddings" folder. It can be used with other models, but the effectiveness is not certain.
Tags: license:other, size_categories:n<1K, format:imagefolder, modality:image... | EasyNegative is a small image-related asset distributed through Hugging Face and described as a negative embedding for use with Stable Diffusion-style image generation workflows. It is intended to be placed in the embeddings folder of stable-diffusion-webui and was trained with Counterfeit, with possible but uncertain ... | huggingface | gsdf/EasyNegative |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: RedPajama-Data-1T
Description: RedPajama is a clean-room, fully open-source implementation of the LLaMa dataset.
Tags: task_categories:text-generation, language:en, size_categories:1M<n<10M, modality:text, library:datasets, library:mlcroissant, region:us
Downloads: 2123
Likes: 1151 | RedPajama-Data-1T is an English text dataset created as a fully open-source, clean-room reproduction of the data mixture used for training LLaMA-like language models. It is intended primarily for large-scale text generation model pretraining and related foundation model research. The dataset is text modality, very larg... | huggingface | togethercomputer/RedPajama-Data-1T |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: medical-o1-reasoning-SFT
Description: News
[2025/04/22] We split the data and kept only the medical SFT dataset (medical_o1_sft.json). The file medical_o1_sft_mix.json contains a mix of medical and general instruction data.
[2025/02/22] We released the distilled dataset from Deepseek-R1 based on medical verifiabl... | medical-o1-reasoning-SFT is a bilingual English-Chinese text dataset for supervised fine-tuning on medical reasoning tasks. It focuses on verifiable medical problems and includes LLM-derived or distilled reasoning chains, making it useful for question answering, instruction tuning, and reasoning-focused model initializ... | huggingface | FreedomIntelligence/medical-o1-reasoning-SFT |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: fineweb-edu
Description: 1.3 trillion tokens of educational web data filtered from FineWeb using an educational quality classifier. English, text/tabular, parquet format.
Tags: task_categories:text-generation, language:en, license:odc-by, size_categories:1B<n<10B, format:parquet, modality:tabular, modality:text, ... | fineweb-edu is a large-scale English educational web dataset from Hugging Face, designed for text generation and language model pretraining. It contains about 1.3 trillion tokens of educational content filtered from FineWeb using a classifier trained from Llama3-70B-Instruct-generated annotations. The dataset is availa... | huggingface | HuggingFaceFW/fineweb-edu |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: dolma
Description: Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Tags: task_categories:text-generation, language:en, license:odc-by, size_categories:n>1T, arxiv:2402.00159, arxiv:2301.13688, region:us, language-modeling, casual-lm, llm
Downloads: 3087
Likes: 1021 | dolma is an open English corpus built for language model pretraining research. It is extremely large in scale, with over three trillion tokens, and is intended for text generation and broader LLM research. The dataset is licensed under ODC-By and is linked to research such as arXiv:2402.00159. Its tags indicate relevan... | huggingface | allenai/dolma |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: the-stack
Description: The Stack is a near-deduplicated code dataset. Initial release included 30 programming languages and 18 permissive licenses; later versions excluded weak copyleft licenses and expanded permissive licenses. Resulting dataset is about 3TB.
Tags: task_categories:text-generation, language_creat... | the-stack is a large multilingual code dataset created for text generation and code model training. It consists of near-deduplicated source code collected across many programming languages and license types, with later releases refining the license set to focus on permissive terms. The dataset is distributed in parquet... | huggingface | bigcode/the-stack |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: TinyStories
Description: Synthetic short stories generated by GPT-3.5 and GPT-4 using a small vocabulary. Intended for training small language models and described in arXiv:2305.07759.
Tags: task_categories:text-generation, language:en, license:cdla-sharing-1.0, size_categories:1M<n<10M, format:parquet, modality:... | TinyStories is an English text dataset of synthetic short stories generated by GPT-3.5 and GPT-4 using intentionally simple vocabulary. It is primarily used for training and evaluating small language models, as described in arXiv:2305.07759. The dataset is relatively compact, in the 1M to 10M size range, and is distrib... | huggingface | roneneldan/TinyStories |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: databricks-dolly-15k
Description: Open instruction-following dataset created by Databricks employees across categories such as brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization.
Tags: task_categories:question-answering, task_categories:summarization, language... | databricks-dolly-15k is an English instruction-following dataset composed of about 15,000 human-generated records created by Databricks employees. It spans multiple behavioral categories, including brainstorming, classification, question answering, generation, information extraction, and summarization, making it well s... | huggingface | databricks/databricks-dolly-15k |
Summarize the given dataset entry, including its purpose, modality, license, scale, and notable usage context. | Name: alpaca
Source: huggingface
ID: tatsu-lab/alpaca
Description: Alpaca is a dataset of 52,000 instructions and demonstrations generated by OpenAI's text-davinci-003 engine. This instruction data can be used to conduct instruction-tuning for language models and make the language model follow instruction better. The a... | Alpaca is a Hugging Face text dataset designed for instruction tuning. It contains about 52,000 instruction-response demonstrations generated with text-davinci-003 and extends the Self-Instruct data generation approach. The dataset is in English, uses the CC-BY-NC-4.0 license, and falls in the 10K to 100K size range. I... | huggingface | tatsu-lab/alpaca |
Summarize the given dataset entry, including its purpose, modality, license, scale, and notable usage context. | Name: bad_prompt
Source: huggingface
ID: Nerfgun3/bad_prompt
Description: Negative Embedding / Textual Inversion. The idea behind this embedding was to train the negative prompt as an embedding, unifying the basis of the negative prompt into one word or embedding. The embedding has been noted as helpful for generation ... | bad_prompt is a Hugging Face image-related dataset/resource focused on negative embedding or textual inversion for Stable Diffusion workflows. Its purpose is to compress a negative prompt into a reusable embedding token, with reported usefulness for improving hand generation. The resource is in English, uses the Creati... | huggingface | Nerfgun3/bad_prompt |
Summarize the dataset and list its key metadata including source, name, description, tags, downloads, likes, and license if available. | Dataset source: huggingface
Dataset id: tiiuae/falcon-refinedweb
Dataset name: falcon-refinedweb
Description: Falcon RefinedWeb is a massive English web dataset built by TII and released under an ODC-By 1.0 license. RefinedWeb is built through stringent filtering and large-scale deduplication of CommonCrawl; models tra... | Falcon RefinedWeb is a large English web dataset from TII hosted on Hugging Face. It is designed for text generation and built from CommonCrawl using strict filtering and large-scale deduplication. The dataset is described as multimodal-friendly because it includes links and alt text, and it is released under the ODC-B... | huggingface | tiiuae/falcon-refinedweb |
Summarize the dataset and list its key metadata including source, name, description, tags, downloads, likes, and notable characteristics. | Dataset source: huggingface
Dataset id: lmsys/lmsys-chat-1m
Dataset name: lmsys-chat-1m
Description: LMSYS-Chat-1M is a large-scale real-world LLM conversation dataset containing one million conversations with 25 state-of-the-art LLMs. It was collected from 210K unique IP addresses on the Vicuna demo and Chatbot Arena ... | LMSYS-Chat-1M is a real-world conversation dataset on Hugging Face containing one million chats involving 25 modern LLMs. It was collected from 210K unique IP addresses through the Vicuna demo and Chatbot Arena between April and August 2023. Each record includes a conversation ID, model name, conversation text in OpenA... | huggingface | lmsys/lmsys-chat-1m |
Summarize the dataset metadata into a concise description for model training and data cataloging. | Name: ShareGPT_Vicuna_unfiltered
Description: Further cleaning done. Please look through the dataset and ensure that I didn't miss anything. Update: Confirmed working method for training the model: https://huggingface.co/AlekseyKorshuk/vicuna-7b/discussions/4#64346c08ef6d5abefe42c12c Two choices: Removes instances of "... | ShareGPT_Vicuna_unfiltered is an English Hugging Face dataset intended for conversational model training. It is a cleaned version of ShareGPT/Vicuna-style data, with documented training guidance and alternative variants that either remove or retain instances of the phrase "I'm sorry, but." The dataset is licensed under... | huggingface | anon8231489123/ShareGPT_Vicuna_unfiltered |
Summarize the dataset metadata into a concise description for model training and data cataloging. | Name: finepdfs
Description: Liberating 3T of the finest tokens from PDFs. FinePDFs is the largest publicly available corpus sourced exclusively from PDFs, containing about 3 trillion tokens across 475 million documents in 1733 languages. See the full description on the dataset page: https://huggingface.co/datasets/Hugg... | finepdfs is a massive multilingual Hugging Face dataset built exclusively from PDF sources. It contains approximately 3 trillion tokens across 475 million documents in 1,733 languages, making it one of the largest publicly available PDF-derived text corpora for text generation and large-scale language model pretraining... | huggingface | HuggingFaceFW/finepdfs |
Summarize the dataset and highlight its purpose, scale, modality, collection method, licensing context, and notable metadata. | Dataset name: PhysicalAI-Autonomous-Vehicles
Description: PHYSICAL AI AUTONOMOUS VEHICLES
The PhysicalAI-Autonomous-Vehicles dataset provides one of the largest, geographically diverse collections of multi-sensor data empowering AV researchers to build the next generation of Physical AI based end-to-end driving systems... | PhysicalAI-Autonomous-Vehicles is a large-scale autonomous vehicle dataset from NVIDIA focused on training next-generation Physical AI and end-to-end driving systems. It contains geographically diverse multi-sensor driving data and includes about 1,700 hours of driving. Both data collection and labeling were performed ... | huggingface | nvidia/PhysicalAI-Autonomous-Vehicles |
Summarize the dataset and highlight its purpose, content domains, size, format, licensing, and notable metadata. | Dataset name: OpenThoughts-114k
Description: Open-Thoughts-114k
Open synthetic reasoning dataset with 114k high-quality examples covering math, science, code, and puzzles.
Available subset: default subset containing ready-to-train data used to finetune the OpenThinker-7B and OpenThinker-32B models.
Tags: license:apache... | OpenThoughts-114k is a synthetic text reasoning dataset designed for supervised fine-tuning and contains 114,000 high-quality examples. Its content spans math, science, code, and puzzles, making it broadly useful for training reasoning-capable language models. The default subset is ready to train on and was used to fin... | huggingface | open-thoughts/OpenThoughts-114k |
Summarize the dataset for instruction-tuning use. | Name: OpenHermes-2.5
Source: huggingface
ID: teknium/OpenHermes-2.5
Description: This is the dataset that made OpenHermes 2.5 and Nous Hermes 2 series of models. It is an exact compilation and curation of many open source datasets and custom synthetic datasets used to advance SOTA LLMs.
Tags: language:eng, size_categor... | OpenHermes-2.5 is a large English text dataset on Hugging Face designed for LLM training and instruction tuning. It contains between 1M and 10M examples in JSON format and is described as the data compilation behind the OpenHermes 2.5 and Nous Hermes 2 model series. The dataset is built from a mixture of open-source an... | huggingface | teknium/OpenHermes-2.5 |
Summarize the dataset for instruction-tuning use. | Name: alpaca-cleaned
Source: huggingface
ID: yahma/alpaca-cleaned
Description: This is a cleaned version of the original Alpaca Dataset released by Stanford. It fixes issues in the original release, including hallucination-prone instructions that referenced internet data.
Tags: task_categories:text-generation, language... | alpaca-cleaned is an English instruction-finetuning dataset on Hugging Face derived from Stanford's original Alpaca release. It is a cleaned version intended to improve data quality by fixing known problems such as instructions that encouraged hallucinated answers by referring to unavailable internet content. The datas... | huggingface | yahma/alpaca-cleaned |
Summarize the dataset metadata into a concise description for machine learning practitioners. | Name: hle
Source: huggingface
Dataset ID: cais/hle
Description: Humanity's Last Exam (HLE) is a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. It consists of 2,500 questions across dozens of subjects. Important ... | hle is an official Hugging Face benchmark dataset from cais/hle. It is a multimodal academic benchmark combining text and image modalities, with 2,500 closed-ended questions spanning dozens of subjects at the frontier of human knowledge. The dataset is distributed in Parquet format, licensed under MIT, and is compatibl... | huggingface | cais/hle |
Summarize the dataset metadata into a concise description for machine learning practitioners. | Name: fineweb-2
Source: huggingface
Dataset ID: HuggingFaceFW/fineweb-2
Description: FineWeb2 is the second iteration of the FineWeb dataset, providing high-quality pretraining data for over 1000 languages. It is fully reproducible, available under the permissive ODC-By 1.0 license, and extensively validated through hu... | fineweb-2 is a large-scale Hugging Face pretraining dataset from HuggingFaceFW designed for text generation. It is the second iteration of FineWeb and provides high-quality, reproducible multilingual text data covering over 1000 languages. The dataset is licensed under ODC-By 1.0, includes text and tabular modalities, ... | huggingface | HuggingFaceFW/fineweb-2 |
Summarize the dataset based on its metadata, including its purpose, modality, likely use cases, language, license, scale, and notable popularity signals. | {"source":"huggingface","id":"ILSVRC/imagenet-1k","name":"imagenet-1k","description":"ILSVRC 2012, commonly known as 'ImageNet' is an image dataset organized according to the WordNet hierarchy. Each meaningful concept in WordNet, possibly described by multiple words or word phrases, is called a synset. ImageNet aims to... | ImageNet-1k is a large-scale image classification dataset hosted on Hugging Face. It contains images organized by WordNet synsets and is intended for multi-class image classification tasks. The dataset modality is image, the primary language tag is English, and it is marked as monolingual. It appears to be an original ... | huggingface | ILSVRC/imagenet-1k |
Summarize the dataset based on its metadata, including its purpose, supported languages, license, likely use cases, and popularity. | {"source":"huggingface","id":"QingyiSi/Alpaca-CoT","name":"Alpaca-CoT","description":"Instruction-Finetuning Dataset Collection (Alpaca-CoT). This repository continuously collects various instruction tuning datasets and standardizes them into the same format, which can be directly loaded by Alpaca model code.","tags":[... | Alpaca-CoT is an instruction-finetuning dataset collection designed to aggregate and standardize multiple instruction tuning datasets into a unified format compatible with Alpaca-style model training. It supports multiple languages, including English and Chinese, and is also tagged as multilingual. The dataset is espec... | huggingface | QingyiSi/Alpaca-CoT |
Summarize the dataset and highlight its purpose, scale, languages, tasks, format, license, and notable characteristics. | Dataset name: PersonaHub
Description: Scaling Synthetic Data Creation with 1,000,000,000 Personas. This repo releases data introduced in the paper "Scaling Synthetic Data Creation with 1,000,000,000 Personas". It proposes a persona-driven data synthesis methodology that leverages various perspectives within a large lan... | PersonaHub is a Hugging Face dataset focused on persona-driven synthetic data creation. It accompanies the paper "Scaling Synthetic Data Creation with 1,000,000,000 Personas" and introduces PERSONA HUB, a large collection of personas automatically curated from web data to support diverse data synthesis with LLMs. The d... | huggingface | proj-persona/PersonaHub |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: prompts.chat
Description: a.k.a. Awesome ChatGPT Prompts. This is a Dataset Repository mirror of prompts.chat — a social platform for AI prompts. prompts.chat is an open-source platform where users can share, discover, and collect AI prompts from the community.
Tags: task_categories:question-answering, task_categ... | prompts.chat is a community-curated prompt dataset mirrored from the prompts.chat platform and associated with the Awesome ChatGPT Prompts project. It contains text-based prompt content for question answering and text generation, with a relatively small size of 1K to 10K records in CSV format. The dataset is licensed u... | huggingface | fka/prompts.chat |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: fineweb
Description: FineWeb consists of more than 18.5T tokens of cleaned and deduplicated English web data from CommonCrawl. The data processing pipeline is optimized for LLM performance and ran on the datatrove library. It was originally meant to be a fully open replication of RefinedWeb.
Tags: task_categories... | FineWeb is a massive English web-scale corpus derived from CommonCrawl, containing over 18.5 trillion cleaned and deduplicated tokens. It is designed primarily for large-scale language model pretraining rather than direct instruction tuning. The dataset is optimized for LLM performance through a dedicated processing pi... | huggingface | HuggingFaceFW/fineweb |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: hh-rlhf
Description: This repository provides access to human preference data about helpfulness and harmlessness from Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. These data are meant to train preference or reward models for subsequent RLHF training and are not meant ... | HH-RLHF is a human feedback dataset created for training reward or preference models focused on helpfulness and harmlessness. It contains text data in JSON format and is medium-scale, with between 100K and 1M examples. Its primary use is in RLHF pipelines rather than standard supervised fine-tuning, and the dataset car... | huggingface | Anthropic/hh-rlhf |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: OpenOrca
Description: The OpenOrca dataset is a rich collection of augmented FLAN data aligned as closely as possible with the distributions outlined in the Orca paper. It has been instrumental in generating high-performing model checkpoints and serves as a valuable resource for NLP researchers and developers.
Ta... | OpenOrca is a large English instruction-style dataset built from augmented FLAN data and shaped to resemble the distributions described in the Orca work. It spans many NLP task types, including question answering, summarization, classification, feature extraction, and text generation, and is distributed in Parquet form... | huggingface | Open-Orca/OpenOrca |
Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training. | Name: oasst1
Description: OpenAssistant Conversations Dataset (OASST1) is a human-generated, human-annotated assistant-style conversation corpus consisting of 161,443 messages in 35 different languages, annotated with 461,292 quality ratings and over 10,000 fully annotated conversation trees.
Tags: language:en, languag... | OASST1 is a multilingual assistant conversation dataset created through human generation and annotation, containing over 161K messages across 35 languages and more than 10,000 annotated conversation trees. It also includes extensive quality ratings, making it useful for both supervised fine-tuning and preference-aware ... | huggingface | OpenAssistant/oasst1 |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: gsm8k
Description: Dataset Card for GSM8K
Dataset Summary
GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems. The dataset was created to support the task of question answering on basic mathematical problems that require multi-step reasoning.
The... | GSM8K is a high-quality English text dataset of grade school math word problems designed for multi-step reasoning and question answering. It contains roughly 8.5K examples, with problems typically requiring 2 to 8 reasoning steps and basic arithmetic operations to solve. The dataset is commonly used as an official benc... | huggingface | openai/gsm8k |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: wikipedia
Description: Dataset Card for Wikimedia Wikipedia
Dataset Summary
Wikipedia dataset containing cleaned articles of all languages.
The dataset is built from the Wikipedia dumps (https://dumps.wikimedia.org/)
with one subset per language, each containing a single train split.
Each example contains the co... | Wikimedia Wikipedia is a massive multilingual text dataset containing cleaned full articles from Wikipedia across a very large number of languages. Built from official Wikipedia dumps, it provides one subset per language and is suitable for language modeling, masked language modeling, text generation, pretraining, and ... | huggingface | wikimedia/wikipedia |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: EasyNegative
Description: Negative Embedding
This is a Negative Embedding trained with Counterfeit. Please use it in the "stable-diffusion-webui/embeddings" folder. It can be used with other models, but the effectiveness is not certain.
Tags: license:other, size_categories:n<1K, format:imagefolder, modality:image... | EasyNegative is a small image-related asset distributed through Hugging Face and described as a negative embedding for use with Stable Diffusion-style image generation workflows. It is intended to be placed in the embeddings folder of stable-diffusion-webui and was trained with Counterfeit, with possible but uncertain ... | huggingface | gsdf/EasyNegative |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: RedPajama-Data-1T
Description: RedPajama is a clean-room, fully open-source implementation of the LLaMa dataset.
Tags: task_categories:text-generation, language:en, size_categories:1M<n<10M, modality:text, library:datasets, library:mlcroissant, region:us
Downloads: 2123
Likes: 1151 | RedPajama-Data-1T is an English text dataset created as a fully open-source, clean-room reproduction of the data mixture used for training LLaMA-like language models. It is intended primarily for large-scale text generation model pretraining and related foundation model research. The dataset is text modality, very larg... | huggingface | togethercomputer/RedPajama-Data-1T |
Summarize the following dataset for supervised fine-tuning metadata generation. Include its purpose, modality, language scope, likely use cases, and notable attributes such as license, scale, and popularity. | Name: medical-o1-reasoning-SFT
Description: News
[2025/04/22] We split the data and kept only the medical SFT dataset (medical_o1_sft.json). The file medical_o1_sft_mix.json contains a mix of medical and general instruction data.
[2025/02/22] We released the distilled dataset from Deepseek-R1 based on medical verifiabl... | medical-o1-reasoning-SFT is a bilingual English-Chinese text dataset for supervised fine-tuning on medical reasoning tasks. It focuses on verifiable medical problems and includes LLM-derived or distilled reasoning chains, making it useful for question answering, instruction tuning, and reasoning-focused model initializ... | huggingface | FreedomIntelligence/medical-o1-reasoning-SFT |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: fineweb-edu
Description: 1.3 trillion tokens of educational web data filtered from FineWeb using an educational quality classifier. English, text/tabular, parquet format.
Tags: task_categories:text-generation, language:en, license:odc-by, size_categories:1B<n<10B, format:parquet, modality:tabular, modality:text, ... | fineweb-edu is a large-scale English educational web dataset from Hugging Face, designed for text generation and language model pretraining. It contains about 1.3 trillion tokens of educational content filtered from FineWeb using a classifier trained from Llama3-70B-Instruct-generated annotations. The dataset is availa... | huggingface | HuggingFaceFW/fineweb-edu |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: dolma
Description: Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Tags: task_categories:text-generation, language:en, license:odc-by, size_categories:n>1T, arxiv:2402.00159, arxiv:2301.13688, region:us, language-modeling, casual-lm, llm
Downloads: 3087
Likes: 1021 | dolma is an open English corpus built for language model pretraining research. It is extremely large in scale, with over three trillion tokens, and is intended for text generation and broader LLM research. The dataset is licensed under ODC-By and is linked to research such as arXiv:2402.00159. Its tags indicate relevan... | huggingface | allenai/dolma |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: the-stack
Description: The Stack is a near-deduplicated code dataset. Initial release included 30 programming languages and 18 permissive licenses; later versions excluded weak copyleft licenses and expanded permissive licenses. Resulting dataset is about 3TB.
Tags: task_categories:text-generation, language_creat... | the-stack is a large multilingual code dataset created for text generation and code model training. It consists of near-deduplicated source code collected across many programming languages and license types, with later releases refining the license set to focus on permissive terms. The dataset is distributed in parquet... | huggingface | bigcode/the-stack |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: TinyStories
Description: Synthetic short stories generated by GPT-3.5 and GPT-4 using a small vocabulary. Intended for training small language models and described in arXiv:2305.07759.
Tags: task_categories:text-generation, language:en, license:cdla-sharing-1.0, size_categories:1M<n<10M, format:parquet, modality:... | TinyStories is an English text dataset of synthetic short stories generated by GPT-3.5 and GPT-4 using intentionally simple vocabulary. It is primarily used for training and evaluating small language models, as described in arXiv:2305.07759. The dataset is relatively compact, in the 1M to 10M size range, and is distrib... | huggingface | roneneldan/TinyStories |
Summarize the dataset and highlight its purpose, scale, modality, language, license, notable tags, and popularity. | Name: databricks-dolly-15k
Description: Open instruction-following dataset created by Databricks employees across categories such as brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization.
Tags: task_categories:question-answering, task_categories:summarization, language... | databricks-dolly-15k is an English instruction-following dataset composed of about 15,000 human-generated records created by Databricks employees. It spans multiple behavioral categories, including brainstorming, classification, question answering, generation, information extraction, and summarization, making it well s... | huggingface | databricks/databricks-dolly-15k |
Summarize the given dataset entry, including its purpose, modality, license, scale, and notable usage context. | Name: alpaca
Source: huggingface
ID: tatsu-lab/alpaca
Description: Alpaca is a dataset of 52,000 instructions and demonstrations generated by OpenAI's text-davinci-003 engine. This instruction data can be used to conduct instruction-tuning for language models and make the language model follow instruction better. The a... | Alpaca is a Hugging Face text dataset designed for instruction tuning. It contains about 52,000 instruction-response demonstrations generated with text-davinci-003 and extends the Self-Instruct data generation approach. The dataset is in English, uses the CC-BY-NC-4.0 license, and falls in the 10K to 100K size range. I... | huggingface | tatsu-lab/alpaca |
Summarize the given dataset entry, including its purpose, modality, license, scale, and notable usage context. | Name: bad_prompt
Source: huggingface
ID: Nerfgun3/bad_prompt
Description: Negative Embedding / Textual Inversion. The idea behind this embedding was to train the negative prompt as an embedding, unifying the basis of the negative prompt into one word or embedding. The embedding has been noted as helpful for generation ... | bad_prompt is a Hugging Face image-related dataset/resource focused on negative embedding or textual inversion for Stable Diffusion workflows. Its purpose is to compress a negative prompt into a reusable embedding token, with reported usefulness for improving hand generation. The resource is in English, uses the Creati... | huggingface | Nerfgun3/bad_prompt |
Summarize the dataset and list its key metadata including source, name, description, tags, downloads, likes, and license if available. | Dataset source: huggingface
Dataset id: tiiuae/falcon-refinedweb
Dataset name: falcon-refinedweb
Description: Falcon RefinedWeb is a massive English web dataset built by TII and released under an ODC-By 1.0 license. RefinedWeb is built through stringent filtering and large-scale deduplication of CommonCrawl; models tra... | Falcon RefinedWeb is a large English web dataset from TII hosted on Hugging Face. It is designed for text generation and built from CommonCrawl using strict filtering and large-scale deduplication. The dataset is described as multimodal-friendly because it includes links and alt text, and it is released under the ODC-B... | huggingface | tiiuae/falcon-refinedweb |
Summarize the dataset and list its key metadata including source, name, description, tags, downloads, likes, and notable characteristics. | Dataset source: huggingface
Dataset id: lmsys/lmsys-chat-1m
Dataset name: lmsys-chat-1m
Description: LMSYS-Chat-1M is a large-scale real-world LLM conversation dataset containing one million conversations with 25 state-of-the-art LLMs. It was collected from 210K unique IP addresses on the Vicuna demo and Chatbot Arena ... | LMSYS-Chat-1M is a real-world conversation dataset on Hugging Face containing one million chats involving 25 modern LLMs. It was collected from 210K unique IP addresses through the Vicuna demo and Chatbot Arena between April and August 2023. Each record includes a conversation ID, model name, conversation text in OpenA... | huggingface | lmsys/lmsys-chat-1m |
Summarize the dataset metadata into a concise description for model training and data cataloging. | Name: ShareGPT_Vicuna_unfiltered
Description: Further cleaning done. Please look through the dataset and ensure that I didn't miss anything. Update: Confirmed working method for training the model: https://huggingface.co/AlekseyKorshuk/vicuna-7b/discussions/4#64346c08ef6d5abefe42c12c Two choices: Removes instances of "... | ShareGPT_Vicuna_unfiltered is an English Hugging Face dataset intended for conversational model training. It is a cleaned version of ShareGPT/Vicuna-style data, with documented training guidance and alternative variants that either remove or retain instances of the phrase "I'm sorry, but." The dataset is licensed under... | huggingface | anon8231489123/ShareGPT_Vicuna_unfiltered |
Summarize the dataset metadata into a concise description for model training and data cataloging. | Name: finepdfs
Description: Liberating 3T of the finest tokens from PDFs. FinePDFs is the largest publicly available corpus sourced exclusively from PDFs, containing about 3 trillion tokens across 475 million documents in 1733 languages. See the full description on the dataset page: https://huggingface.co/datasets/Hugg... | finepdfs is a massive multilingual Hugging Face dataset built exclusively from PDF sources. It contains approximately 3 trillion tokens across 475 million documents in 1,733 languages, making it one of the largest publicly available PDF-derived text corpora for text generation and large-scale language model pretraining... | huggingface | HuggingFaceFW/finepdfs |
Summarize the dataset and highlight its purpose, scale, modality, collection method, licensing context, and notable metadata. | Dataset name: PhysicalAI-Autonomous-Vehicles
Description: PHYSICAL AI AUTONOMOUS VEHICLES
The PhysicalAI-Autonomous-Vehicles dataset provides one of the largest, geographically diverse collections of multi-sensor data empowering AV researchers to build the next generation of Physical AI based end-to-end driving systems... | PhysicalAI-Autonomous-Vehicles is a large-scale autonomous vehicle dataset from NVIDIA focused on training next-generation Physical AI and end-to-end driving systems. It contains geographically diverse multi-sensor driving data and includes about 1,700 hours of driving. Both data collection and labeling were performed ... | huggingface | nvidia/PhysicalAI-Autonomous-Vehicles |
Summarize the dataset and highlight its purpose, content domains, size, format, licensing, and notable metadata. | Dataset name: OpenThoughts-114k
Description: Open-Thoughts-114k
Open synthetic reasoning dataset with 114k high-quality examples covering math, science, code, and puzzles.
Available subset: default subset containing ready-to-train data used to finetune the OpenThinker-7B and OpenThinker-32B models.
Tags: license:apache... | OpenThoughts-114k is a synthetic text reasoning dataset designed for supervised fine-tuning and contains 114,000 high-quality examples. Its content spans math, science, code, and puzzles, making it broadly useful for training reasoning-capable language models. The default subset is ready to train on and was used to fin... | huggingface | open-thoughts/OpenThoughts-114k |
Summarize the dataset for instruction-tuning use. | Name: OpenHermes-2.5
Source: huggingface
ID: teknium/OpenHermes-2.5
Description: This is the dataset that made OpenHermes 2.5 and Nous Hermes 2 series of models. It is an exact compilation and curation of many open source datasets and custom synthetic datasets used to advance SOTA LLMs.
Tags: language:eng, size_categor... | OpenHermes-2.5 is a large English text dataset on Hugging Face designed for LLM training and instruction tuning. It contains between 1M and 10M examples in JSON format and is described as the data compilation behind the OpenHermes 2.5 and Nous Hermes 2 model series. The dataset is built from a mixture of open-source an... | huggingface | teknium/OpenHermes-2.5 |
Summarize the dataset for instruction-tuning use. | Name: alpaca-cleaned
Source: huggingface
ID: yahma/alpaca-cleaned
Description: This is a cleaned version of the original Alpaca Dataset released by Stanford. It fixes issues in the original release, including hallucination-prone instructions that referenced internet data.
Tags: task_categories:text-generation, language... | alpaca-cleaned is an English instruction-finetuning dataset on Hugging Face derived from Stanford's original Alpaca release. It is a cleaned version intended to improve data quality by fixing known problems such as instructions that encouraged hallucinated answers by referring to unavailable internet content. The datas... | huggingface | yahma/alpaca-cleaned |
Summarize the dataset metadata into a concise description for machine learning practitioners. | Name: hle
Source: huggingface
Dataset ID: cais/hle
Description: Humanity's Last Exam (HLE) is a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. It consists of 2,500 questions across dozens of subjects. Important ... | hle is an official Hugging Face benchmark dataset from cais/hle. It is a multimodal academic benchmark combining text and image modalities, with 2,500 closed-ended questions spanning dozens of subjects at the frontier of human knowledge. The dataset is distributed in Parquet format, licensed under MIT, and is compatibl... | huggingface | cais/hle |
Summarize the dataset metadata into a concise description for machine learning practitioners. | Name: fineweb-2
Source: huggingface
Dataset ID: HuggingFaceFW/fineweb-2
Description: FineWeb2 is the second iteration of the FineWeb dataset, providing high-quality pretraining data for over 1000 languages. It is fully reproducible, available under the permissive ODC-By 1.0 license, and extensively validated through hu... | fineweb-2 is a large-scale Hugging Face pretraining dataset from HuggingFaceFW designed for text generation. It is the second iteration of FineWeb and provides high-quality, reproducible multilingual text data covering over 1000 languages. The dataset is licensed under ODC-By 1.0, includes text and tabular modalities, ... | huggingface | HuggingFaceFW/fineweb-2 |
Summarize the dataset based on its metadata, including its purpose, modality, likely use cases, language, license, scale, and notable popularity signals. | {"source":"huggingface","id":"ILSVRC/imagenet-1k","name":"imagenet-1k","description":"ILSVRC 2012, commonly known as 'ImageNet' is an image dataset organized according to the WordNet hierarchy. Each meaningful concept in WordNet, possibly described by multiple words or word phrases, is called a synset. ImageNet aims to... | ImageNet-1k is a large-scale image classification dataset hosted on Hugging Face. It contains images organized by WordNet synsets and is intended for multi-class image classification tasks. The dataset modality is image, the primary language tag is English, and it is marked as monolingual. It appears to be an original ... | huggingface | ILSVRC/imagenet-1k |
Summarize the dataset based on its metadata, including its purpose, supported languages, license, likely use cases, and popularity. | {"source":"huggingface","id":"QingyiSi/Alpaca-CoT","name":"Alpaca-CoT","description":"Instruction-Finetuning Dataset Collection (Alpaca-CoT). This repository continuously collects various instruction tuning datasets and standardizes them into the same format, which can be directly loaded by Alpaca model code.","tags":[... | Alpaca-CoT is an instruction-finetuning dataset collection designed to aggregate and standardize multiple instruction tuning datasets into a unified format compatible with Alpaca-style model training. It supports multiple languages, including English and Chinese, and is also tagged as multilingual. The dataset is espec... | huggingface | QingyiSi/Alpaca-CoT |
Summarize the dataset and highlight its purpose, scale, languages, tasks, format, license, and notable characteristics. | Dataset name: PersonaHub
Description: Scaling Synthetic Data Creation with 1,000,000,000 Personas. This repo releases data introduced in the paper "Scaling Synthetic Data Creation with 1,000,000,000 Personas". It proposes a persona-driven data synthesis methodology that leverages various perspectives within a large lan... | PersonaHub is a Hugging Face dataset focused on persona-driven synthetic data creation. It accompanies the paper "Scaling Synthetic Data Creation with 1,000,000,000 Personas" and introduces PERSONA HUB, a large collection of personas automatically curated from web data to support diverse data synthesis with LLMs. The d... | huggingface | proj-persona/PersonaHub |
SoloAI SFT Dataset: 20260426-1343
📊 数据集概览
| 属性 | 值 |
|---|---|
| 数据条数 | 30 条 |
| 数据源 | huggingface |
| 生成时间 | 2026-04-26 13:43 |
| 格式 | Instruction-Input-Output |
| 主要用途 | SFT 微调 / 指令调优 |
🎯 适用场景
- LLM 指令微调 (Instruction Tuning): 适用于训练对话型 AI 助手
- Prompt Engineering 研究: 可用于分析和优化提示词设计
- 多语言支持: 包含英文和中文数据
📝 数据格式
每条数据包含三个字段：
instruction: 任务指令（描述需要完成的任务）input: 输入上下文（提供任务相关的背景信息）output: 期望输出（模型应生成的回答）
示例
{'instruction': 'Summarize the dataset for supervised fine-tuning use, including its purpose, content type, notable characteristics, and likely relevance to LLM training.', 'input': 'Name: prompts.chat\nDescription: a.k.a. Awesome ChatGPT Prompts. This is a Dataset Repository mirror of prompts.chat — a social platform for AI prompts. prompts.chat is an open-source platform where users can share, discover, and collect AI prompts from the community.\nTags: task_categories:question-answering, task_categories:text-generation, license:cc0-1.0, size_categories:1K<n<10K, format:csv, modality:text, region:us, ChatGPT, prompts, AI, GPT, Claude, Gemini, Llama, Mistral, LLM, prompt-engineering, conversational-ai, text-generation, chatbot, awesome-list\nDownloads: 47783\nLikes: 9680', 'output': 'prompts.chat is a community-curated prompt dataset mirrored from the prompts.chat platform and associated with the Awesome ChatGPT Prompts project. It contains text-based prompt content for question answering and text generation, with a relatively small size of 1K to 10K records in CSV format. The dataset is licensed under CC0-1.0, making it easy to reuse. Its main value for LLM work is as a prompt engineering and prompt collection resource rather than a conventional supervised response dataset. It is especially relevant for studying prompt design patterns across systems such as ChatGPT, Claude, Gemini, Llama, and Mistral.', 'source': 'huggingface', 'original_id': 'fka/prompts.chat'}
🤖 数据来源
本数据集由 SoloAI 自动化数据管道生成：
- 从 HuggingFace Datasets Hub 发现高质量数据集
- AI 清洗为 SFT 格式（Instruction-Input-Output）
- 质量过滤后发布
⚠️ 使用说明 & 📬 商务联系
- 本数据集仅供研究和实验用途
- 请遵守原始数据的许可证要求
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- 📧 请联系:
379744050@qq.com - 🤖 SoloAI 提供高质量 SFT 数据定制服务。
- 建议邮件标题:
【数据定制咨询】行业 + 数据类型 + 规模 - 建议正文包含: 目标用途、需要条数、语言、字段格式、预算、交付时间
- 📧 请联系:
💰 商业合作报价
| 套餐 | 价格 | 说明 |
|---|---|---|
| Starter | $199 / 1000条高质量 SFT 数据 | 适合个人开发者 / 小团队 |
| Growth | $499 / 5000条行业数据 | 适合垂直行业训练数据 |
| Enterprise | $1499 / 定制领域数据管道 | 适合长期定制与数据管道 |
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- 可从单次交付升级为长期数据管道合作
📈 更新日志
| 版本 | 日期 | 说明 |
|---|---|---|
| v1.0 | 2026-04-26 13:43 | 初始发布，30 条数据 |
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