instruction stringlengths 44 148 | input stringlengths 347 1.09k | output stringlengths 293 739 | source stringclasses 1
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Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"fka/prompts.chat","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.... | prompts.chat is a community prompt dataset mirrored from the prompts.chat platform and associated Awesome ChatGPT Prompts collection. It focuses on user-shared prompts for systems such as ChatGPT, Claude, Gemini, Llama, and Mistral. The dataset is relatively small, in the 1K to 10K range, stored as CSV text data, and l... | huggingface | fka/prompts.chat |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"HuggingFaceFW/fineweb","name":"fineweb","description":"FineWeb is a large-scale dataset of cleaned and deduplicated English web data from CommonCrawl, consisting of more than 18.5T tokens and built with a pipeline optimized for LLM performance.","tags":["task_categories:text-generation","l... | FineWeb is a massive English web-text corpus derived from CommonCrawl and processed through a cleaning and deduplication pipeline designed for strong LLM pretraining performance. It contains more than 18.5 trillion tokens, making it one of the largest openly available web datasets for language modeling. The dataset is ... | huggingface | HuggingFaceFW/fineweb |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"Anthropic/hh-rlhf","name":"hh-rlhf","description":"This repository provides human preference data about helpfulness and harmlessness for training reward or preference models in RLHF, along with related conversation data. The card notes these data are not meant for supervised training of di... | HH-RLHF is a human feedback dataset from Anthropic centered on helpfulness and harmlessness preferences. It is designed primarily for training reward models or preference models used in RLHF pipelines, not for straightforward supervised fine-tuning of assistant responses. The dataset is medium to large in size, between... | huggingface | Anthropic/hh-rlhf |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"Open-Orca/OpenOrca","name":"OpenOrca","description":"The OpenOrca dataset is a rich collection of augmented FLAN data aligned as closely as possible with the distributions described in the Orca paper, and was used to generate strong model checkpoints.","tags":["task_categories:text-classif... | OpenOrca is a large instruction-style dataset built from augmented FLAN data and intended to approximate the distributions described in the Orca work. It is an English text dataset with between 1M and 10M examples, distributed in Parquet format under the MIT license. Likely use cases include supervised fine-tuning of i... | huggingface | Open-Orca/OpenOrca |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"OpenAssistant/oasst1","name":"oasst1","description":"OpenAssistant Conversations Dataset (OASST1) is a human-generated, human-annotated assistant-style conversation corpus with 161,443 messages in 35 languages, 461,292 quality ratings, and over 10,000 fully annotated conversation trees.","... | OASST1 is a multilingual assistant conversation dataset created through human generation and annotation. It contains over 161K messages across 35 languages, along with more than 461K quality ratings and over 10K fully annotated conversation trees. The dataset is released under Apache-2.0, stored in Parquet format, and ... | huggingface | OpenAssistant/oasst1 |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: openai/gsm8k
Name: gsm8k
Description: Dataset Card for GSM8K. 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... | GSM8K is a Hugging Face text dataset of English grade-school math word problems designed for question answering and multi-step reasoning. It contains about 8.5K high-quality problems, typically requiring 2 to 8 reasoning steps and basic arithmetic operations. The dataset is monolingual, crowdsourced, licensed under MIT... | huggingface | openai/gsm8k |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: wikimedia/wikipedia
Name: wikipedia
Description: Dataset Card for Wikimedia Wikipedia. Wikipedia dataset containing cleaned articles of all languages. The dataset is built from the Wikipedia dumps with one subset per language, each containing a single train split. Each example contains the conte... | The Wikimedia Wikipedia dataset is a large multilingual text corpus containing cleaned full Wikipedia articles across hundreds of languages. It is intended for language modeling and masked language modeling tasks, with one language subset per language and a train split for each. Articles are cleaned to remove markdown ... | huggingface | wikimedia/wikipedia |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: gsdf/EasyNegative
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... | EasyNegative is a Hugging Face image-related resource described as a negative embedding for Stable Diffusion workflows, especially for use in the stable-diffusion-webui embeddings folder. It appears to be a very small artifact rather than a conventional dataset, and is associated with image modality and imagefolder for... | huggingface | gsdf/EasyNegative |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: togethercomputer/RedPajama-Data-1T
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
... | RedPajama-Data-1T is an English text dataset intended for text generation and large-scale language model training. It is described as a clean-room, fully open-source implementation of the dataset used for LLaMA-style pretraining. The dataset is large in scale, text-only, and positioned as an open alternative for founda... | huggingface | togethercomputer/RedPajama-Data-1T |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: FreedomIntelligence/medical-o1-reasoning-SFT
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 rele... | medical-o1-reasoning-SFT is a bilingual English and Chinese text dataset for supervised fine-tuning on medical reasoning and question answering tasks. It focuses on medical verifiable problems and includes reasoning chains distilled from DeepSeek-R1. The dataset is intended for SFT and text generation use cases, is dis... | huggingface | FreedomIntelligence/medical-o1-reasoning-SFT |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: fineweb-edu
Source: huggingface
ID: HuggingFaceFW/fineweb-edu
Description: FineWeb-Edu is a 1.3 trillion token educational web dataset filtered from FineWeb using an educational quality classifier. It is intended for text generation and educational data use.
Tags: task_categories:text-generation, language:en, lic... | FineWeb-Edu is a large English educational text dataset on Hugging Face designed for text generation. It contains about 1.3 trillion tokens of web data filtered from FineWeb using an educational quality classifier. The dataset is distributed in parquet format, supports multiple data libraries, uses the ODC-By license, ... | huggingface | HuggingFaceFW/fineweb-edu |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: dolma
Source: huggingface
ID: allenai/dolma
Description: Dolma is 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, ... | Dolma is an English open corpus for language model pretraining research, containing roughly three trillion tokens. It is intended for text generation and LLM training use cases, is licensed under ODC-By, and is positioned as a very large-scale research dataset for pretraining language models. | huggingface | allenai/dolma |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: the-stack
Source: huggingface
ID: bigcode/the-stack
Description: The Stack is a code dataset for language model training. Its releases describe changes in included licenses and programming languages, with a near-deduplicated dataset reaching multi-terabyte scale.
Tags: task_categories:text-generation, language_cr... | The Stack is a multilingual code dataset on Hugging Face built for text generation and code model training. It aggregates source code across many programming languages, tracks license filtering across versions, and provides a near-deduplicated corpus in parquet format for large-scale code LLM development. | huggingface | bigcode/the-stack |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: TinyStories
Source: huggingface
ID: roneneldan/TinyStories
Description: TinyStories contains synthetically generated short stories created by GPT-3.5 and GPT-4 using a small vocabulary. It is described in an associated paper and supports training and validation splits for small language model experiments.
Tags: t... | TinyStories is an English synthetic text dataset made of short stories generated by GPT-3.5 and GPT-4 with a constrained vocabulary. It is suitable for text generation research and small language model training, comes in parquet format, and is commonly used for controlled experiments in language modeling. | huggingface | roneneldan/TinyStories |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: databricks-dolly-15k
Source: huggingface
ID: databricks/databricks-dolly-15k
Description: databricks-dolly-15k is an open instruction-following dataset created by Databricks employees across categories such as brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization... | Databricks Dolly 15k is an English instruction-following dataset consisting of about 15,000 records created by Databricks employees. It covers tasks such as question answering, summarization, brainstorming, classification, and information extraction, making it well suited for supervised fine-tuning of instruction-tuned... | huggingface | databricks/databricks-dolly-15k |
Summarize the dataset and highlight its main purpose, modality, scale, language, license, and notable characteristics. | 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 an English text-generation and instruction-finetuning dataset hosted on Hugging Face. It contains about 52,000 instruction-response demonstrations generated with OpenAI's text-davinci-003 and built on the Self-Instruct data generation pipeline. Its main purpose is to support instruction-tuning so language mod... | huggingface | tatsu-lab/alpaca |
Summarize the dataset and highlight its main purpose, modality, scale, language, license, and notable characteristics. | Name: bad_prompt
Source: huggingface
ID: Nerfgun3/bad_prompt
Description: Negative Embedding / Textual Inversion. The idea behind this embedding was to somehow train the negative prompt as an embedding, thus unifying the basis of the negative prompt into one word or embedding. Side note: Embedding has proven to be very... | bad_prompt is a small English image-related Hugging Face dataset associated with Stable Diffusion workflows. It is described as a negative embedding or textual inversion asset intended to compress negative prompting behavior into a reusable embedding, with noted usefulness for improving hand generation. The dataset is ... | huggingface | Nerfgun3/bad_prompt |
Summarize the dataset metadata into a concise SFT-style description highlighting what the dataset is, key characteristics, and notable metadata. | {"source":"huggingface","id":"tiiuae/falcon-refinedweb","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 trained on it a... | Falcon RefinedWeb is a large-scale English web text dataset from TII hosted on Hugging Face. It is designed for text generation and built from CommonCrawl using stringent filtering and large-scale deduplication. The dataset is notable for strong downstream training performance despite relying only on web data, and it i... | huggingface | tiiuae/falcon-refinedweb |
Summarize the dataset metadata into a concise SFT-style description highlighting what the dataset is, key characteristics, and notable metadata. | {"source":"huggingface","id":"lmsys/lmsys-chat-1m","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 website from... | LMSYS-Chat-1M is a real-world conversational text dataset hosted on Hugging Face, containing one million conversations involving 25 state-of-the-art LLMs. The data was collected from 210,000 unique IP addresses through the Vicuna demo and Chatbot Arena between April and August 2023. Each record includes a conversation ... | huggingface | lmsys/lmsys-chat-1m |
Summarize the dataset metadata into a concise training-data description for supervised fine-tuning. | Name: ShareGPT_Vicuna_unfiltered
Source: huggingface
Dataset ID: anon8231489123/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. Two choices are mentioned: one version removes i... | ShareGPT_Vicuna_unfiltered is an English-language Hugging Face dataset intended for conversational model training and cleaning workflows. It contains a cleaned ShareGPT/Vicuna-style corpus, with variants that either remove or keep instances of the phrase "I'm sorry, but." The dataset is tagged with Apache-2.0 license a... | huggingface | anon8231489123/ShareGPT_Vicuna_unfiltered |
Summarize the dataset metadata into a concise training-data description for supervised fine-tuning. | Name: PhysicalAI-Autonomous-Vehicles
Source: huggingface
Dataset ID: nvidia/PhysicalAI-Autonomous-Vehicles
Description: PHYSICAL AI AUTONOMOUS VEHICLES. The dataset provides one of the largest geographically diverse collections of multi-sensor data for autonomous vehicle researchers building next-generation Physical AI... | PhysicalAI-Autonomous-Vehicles is a large-scale Hugging Face dataset from NVIDIA for autonomous driving and Physical AI research. It includes geographically diverse multi-sensor driving data, collected and labeled through automatic sensor-based processes, totaling about 1700 hours of driving. The dataset is intended fo... | huggingface | nvidia/PhysicalAI-Autonomous-Vehicles |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, scale, languages, format, license, and notable characteristics. | 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.
Tags: task_categories:text-generation; many language tags; license:odc-by; size_ca... | finepdfs is a large-scale Hugging Face dataset built exclusively from PDF sources. It contains roughly 3 trillion tokens spanning about 475 million documents across 1733 languages, making it a highly multilingual corpus for text generation and language model pretraining or fine-tuning. The dataset is distributed in Par... | huggingface | HuggingFaceFW/finepdfs |
Summarize the dataset for supervised fine-tuning use, highlighting domain coverage, scale, format, license, and intended training purpose. | Name: OpenThoughts-114k
Description: Open synthetic reasoning dataset with 114k high-quality examples covering math, science, code, and puzzles. Default subset contains ready-to-train data used to finetune the OpenThinker-7B and OpenThinker-32B models.
Tags: license:apache-2.0; size_categories:100K<n<1M; format:parquet... | OpenThoughts-114k is a synthetic reasoning dataset on Hugging Face with approximately 114,000 high-quality training examples. It covers multiple reasoning-heavy domains, including math, science, code, and puzzles. The default subset is ready to train and was used to fine-tune the OpenThinker-7B and OpenThinker-32B mode... | huggingface | open-thoughts/OpenThoughts-114k |
Summarize the dataset for supervised fine-tuning use. | Name: OpenHermes-2.5
Source: huggingface
Dataset ID: teknium/OpenHermes-2.5
Description: This is the dataset that made OpenHermes 2.5 and Nous Hermes 2 series of models. It is described as the exact compilation and curation of many open source datasets and custom created synthetic datasets underpinning Open Hermes 2/2.... | OpenHermes-2.5 is a large English text dataset on Hugging Face designed for instruction tuning and model distillation. It is a compilation of open-source and synthetic data used to train the OpenHermes 2.5 and Nous Hermes 2 model series. The dataset is distributed in JSON format, tagged as synthetic and GPT-4/distillat... | huggingface | teknium/OpenHermes-2.5 |
Summarize the dataset for supervised fine-tuning use. | Name: alpaca-cleaned
Source: huggingface
Dataset 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, ... | 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 correct known issues such as hallucination-inducing prompts that depended on internet-based information. The dataset supports text generation tasks, is provide... | huggingface | yahma/alpaca-cleaned |
Summarize the dataset metadata into a concise structured description for machine learning use. | {"source":"huggingface","id":"cais/hle","name":"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. Note: ... | {"dataset_name":"hle","full_id":"cais/hle","platform":"Hugging Face","summary":"Humanity's Last Exam is a multimodal benchmark covering broad academic subjects with 2,500 closed-ended questions at the frontier of human knowledge.","modalities":["image","text"],"format":"parquet","license":"mit","size_category":"1K<n<10... | huggingface | cais/hle |
Summarize the dataset metadata into a concise structured description for machine learning use. | {"source":"huggingface","id":"HuggingFaceFW/fineweb-2","name":"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 ODC-By 1.0 license, and validated through extensive ablation ex... | {"dataset_name":"fineweb-2","full_id":"HuggingFaceFW/fineweb-2","platform":"Hugging Face","summary":"FineWeb2 is a large-scale multilingual pretraining dataset covering over 1000 languages, designed for high-quality reproducible text data generation and validated through extensive experiments.","task_categories":["text... | huggingface | HuggingFaceFW/fineweb-2 |
Summarize the dataset and identify its primary machine learning use case. | Name: imagenet-1k
Source: huggingface
Dataset ID: ILSVRC/imagenet-1k
Description: ILSVRC 2012, commonly known as 'ImageNet' is an image dataset organized according to the WordNet hierarchy. Each meaningful concept in WordNet is called a synset. ImageNet aims to provide on average 1000 images to illustrate each synset.
... | ImageNet-1k is a large-scale image dataset from the ILSVRC 2012 benchmark, organized using the WordNet synset hierarchy. It contains images representing many object categories and is widely used for multi-class image classification. The dataset is crowdsourced, English-labeled, image-based, and commonly used for traini... | huggingface | ILSVRC/imagenet-1k |
Summarize the dataset and describe what kind of model training it is intended for. | Name: Alpaca-CoT
Source: huggingface
Dataset ID: QingyiSi/Alpaca-CoT
Description: This repository continuously collects various instruction tuning datasets and standardizes them into the same format, which can be directly loaded by the code of the Alpaca model. It also includes empirical study on various instruction-tu... | Alpaca-CoT is a collection of standardized instruction-tuning datasets designed for direct use with Alpaca-style models. It focuses on instruction-following and chain-of-thought style data, supporting multiple languages including English and Chinese. The dataset is intended for supervised fine-tuning of language models... | huggingface | QingyiSi/Alpaca-CoT |
Summarize the dataset based on its metadata. | Name: PersonaHub
Source: huggingface
ID: proj-persona/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... | PersonaHub is a Hugging Face dataset focused on large-scale synthetic data creation through persona-driven generation. It is associated with the paper "Scaling Synthetic Data Creation with 1,000,000,000 Personas" and introduces a collection of 1 billion diverse personas curated from web data to support varied LLM persp... | huggingface | proj-persona/PersonaHub |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"fka/prompts.chat","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.... | prompts.chat is a community prompt dataset mirrored from the prompts.chat platform and associated Awesome ChatGPT Prompts collection. It focuses on user-shared prompts for systems such as ChatGPT, Claude, Gemini, Llama, and Mistral. The dataset is relatively small, in the 1K to 10K range, stored as CSV text data, and l... | huggingface | fka/prompts.chat |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"HuggingFaceFW/fineweb","name":"fineweb","description":"FineWeb is a large-scale dataset of cleaned and deduplicated English web data from CommonCrawl, consisting of more than 18.5T tokens and built with a pipeline optimized for LLM performance.","tags":["task_categories:text-generation","l... | FineWeb is a massive English web-text corpus derived from CommonCrawl and processed through a cleaning and deduplication pipeline designed for strong LLM pretraining performance. It contains more than 18.5 trillion tokens, making it one of the largest openly available web datasets for language modeling. The dataset is ... | huggingface | HuggingFaceFW/fineweb |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"Anthropic/hh-rlhf","name":"hh-rlhf","description":"This repository provides human preference data about helpfulness and harmlessness for training reward or preference models in RLHF, along with related conversation data. The card notes these data are not meant for supervised training of di... | HH-RLHF is a human feedback dataset from Anthropic centered on helpfulness and harmlessness preferences. It is designed primarily for training reward models or preference models used in RLHF pipelines, not for straightforward supervised fine-tuning of assistant responses. The dataset is medium to large in size, between... | huggingface | Anthropic/hh-rlhf |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"Open-Orca/OpenOrca","name":"OpenOrca","description":"The OpenOrca dataset is a rich collection of augmented FLAN data aligned as closely as possible with the distributions described in the Orca paper, and was used to generate strong model checkpoints.","tags":["task_categories:text-classif... | OpenOrca is a large instruction-style dataset built from augmented FLAN data and intended to approximate the distributions described in the Orca work. It is an English text dataset with between 1M and 10M examples, distributed in Parquet format under the MIT license. Likely use cases include supervised fine-tuning of i... | huggingface | Open-Orca/OpenOrca |
Summarize the dataset for LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics. | {"source":"huggingface","id":"OpenAssistant/oasst1","name":"oasst1","description":"OpenAssistant Conversations Dataset (OASST1) is a human-generated, human-annotated assistant-style conversation corpus with 161,443 messages in 35 languages, 461,292 quality ratings, and over 10,000 fully annotated conversation trees.","... | OASST1 is a multilingual assistant conversation dataset created through human generation and annotation. It contains over 161K messages across 35 languages, along with more than 461K quality ratings and over 10K fully annotated conversation trees. The dataset is released under Apache-2.0, stored in Parquet format, and ... | huggingface | OpenAssistant/oasst1 |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: openai/gsm8k
Name: gsm8k
Description: Dataset Card for GSM8K. 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... | GSM8K is a Hugging Face text dataset of English grade-school math word problems designed for question answering and multi-step reasoning. It contains about 8.5K high-quality problems, typically requiring 2 to 8 reasoning steps and basic arithmetic operations. The dataset is monolingual, crowdsourced, licensed under MIT... | huggingface | openai/gsm8k |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: wikimedia/wikipedia
Name: wikipedia
Description: Dataset Card for Wikimedia Wikipedia. Wikipedia dataset containing cleaned articles of all languages. The dataset is built from the Wikipedia dumps with one subset per language, each containing a single train split. Each example contains the conte... | The Wikimedia Wikipedia dataset is a large multilingual text corpus containing cleaned full Wikipedia articles across hundreds of languages. It is intended for language modeling and masked language modeling tasks, with one language subset per language and a train split for each. Articles are cleaned to remove markdown ... | huggingface | wikimedia/wikipedia |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: gsdf/EasyNegative
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... | EasyNegative is a Hugging Face image-related resource described as a negative embedding for Stable Diffusion workflows, especially for use in the stable-diffusion-webui embeddings folder. It appears to be a very small artifact rather than a conventional dataset, and is associated with image modality and imagefolder for... | huggingface | gsdf/EasyNegative |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: togethercomputer/RedPajama-Data-1T
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
... | RedPajama-Data-1T is an English text dataset intended for text generation and large-scale language model training. It is described as a clean-room, fully open-source implementation of the dataset used for LLaMA-style pretraining. The dataset is large in scale, text-only, and positioned as an open alternative for founda... | huggingface | togethercomputer/RedPajama-Data-1T |
Summarize the dataset or resource based on its metadata, including its purpose, modality, language coverage, license, and notable characteristics. | Source: huggingface
ID: FreedomIntelligence/medical-o1-reasoning-SFT
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 rele... | medical-o1-reasoning-SFT is a bilingual English and Chinese text dataset for supervised fine-tuning on medical reasoning and question answering tasks. It focuses on medical verifiable problems and includes reasoning chains distilled from DeepSeek-R1. The dataset is intended for SFT and text generation use cases, is dis... | huggingface | FreedomIntelligence/medical-o1-reasoning-SFT |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: fineweb-edu
Source: huggingface
ID: HuggingFaceFW/fineweb-edu
Description: FineWeb-Edu is a 1.3 trillion token educational web dataset filtered from FineWeb using an educational quality classifier. It is intended for text generation and educational data use.
Tags: task_categories:text-generation, language:en, lic... | FineWeb-Edu is a large English educational text dataset on Hugging Face designed for text generation. It contains about 1.3 trillion tokens of web data filtered from FineWeb using an educational quality classifier. The dataset is distributed in parquet format, supports multiple data libraries, uses the ODC-By license, ... | huggingface | HuggingFaceFW/fineweb-edu |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: dolma
Source: huggingface
ID: allenai/dolma
Description: Dolma is 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, ... | Dolma is an English open corpus for language model pretraining research, containing roughly three trillion tokens. It is intended for text generation and LLM training use cases, is licensed under ODC-By, and is positioned as a very large-scale research dataset for pretraining language models. | huggingface | allenai/dolma |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: the-stack
Source: huggingface
ID: bigcode/the-stack
Description: The Stack is a code dataset for language model training. Its releases describe changes in included licenses and programming languages, with a near-deduplicated dataset reaching multi-terabyte scale.
Tags: task_categories:text-generation, language_cr... | The Stack is a multilingual code dataset on Hugging Face built for text generation and code model training. It aggregates source code across many programming languages, tracks license filtering across versions, and provides a near-deduplicated corpus in parquet format for large-scale code LLM development. | huggingface | bigcode/the-stack |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: TinyStories
Source: huggingface
ID: roneneldan/TinyStories
Description: TinyStories contains synthetically generated short stories created by GPT-3.5 and GPT-4 using a small vocabulary. It is described in an associated paper and supports training and validation splits for small language model experiments.
Tags: t... | TinyStories is an English synthetic text dataset made of short stories generated by GPT-3.5 and GPT-4 with a constrained vocabulary. It is suitable for text generation research and small language model training, comes in parquet format, and is commonly used for controlled experiments in language modeling. | huggingface | roneneldan/TinyStories |
Summarize the dataset metadata into a concise SFT-friendly description. | Name: databricks-dolly-15k
Source: huggingface
ID: databricks/databricks-dolly-15k
Description: databricks-dolly-15k is an open instruction-following dataset created by Databricks employees across categories such as brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization... | Databricks Dolly 15k is an English instruction-following dataset consisting of about 15,000 records created by Databricks employees. It covers tasks such as question answering, summarization, brainstorming, classification, and information extraction, making it well suited for supervised fine-tuning of instruction-tuned... | huggingface | databricks/databricks-dolly-15k |
Summarize the dataset and highlight its main purpose, modality, scale, language, license, and notable characteristics. | 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 an English text-generation and instruction-finetuning dataset hosted on Hugging Face. It contains about 52,000 instruction-response demonstrations generated with OpenAI's text-davinci-003 and built on the Self-Instruct data generation pipeline. Its main purpose is to support instruction-tuning so language mod... | huggingface | tatsu-lab/alpaca |
Summarize the dataset and highlight its main purpose, modality, scale, language, license, and notable characteristics. | Name: bad_prompt
Source: huggingface
ID: Nerfgun3/bad_prompt
Description: Negative Embedding / Textual Inversion. The idea behind this embedding was to somehow train the negative prompt as an embedding, thus unifying the basis of the negative prompt into one word or embedding. Side note: Embedding has proven to be very... | bad_prompt is a small English image-related Hugging Face dataset associated with Stable Diffusion workflows. It is described as a negative embedding or textual inversion asset intended to compress negative prompting behavior into a reusable embedding, with noted usefulness for improving hand generation. The dataset is ... | huggingface | Nerfgun3/bad_prompt |
Summarize the dataset metadata into a concise SFT-style description highlighting what the dataset is, key characteristics, and notable metadata. | {"source":"huggingface","id":"tiiuae/falcon-refinedweb","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 trained on it a... | Falcon RefinedWeb is a large-scale English web text dataset from TII hosted on Hugging Face. It is designed for text generation and built from CommonCrawl using stringent filtering and large-scale deduplication. The dataset is notable for strong downstream training performance despite relying only on web data, and it i... | huggingface | tiiuae/falcon-refinedweb |
Summarize the dataset metadata into a concise SFT-style description highlighting what the dataset is, key characteristics, and notable metadata. | {"source":"huggingface","id":"lmsys/lmsys-chat-1m","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 website from... | LMSYS-Chat-1M is a real-world conversational text dataset hosted on Hugging Face, containing one million conversations involving 25 state-of-the-art LLMs. The data was collected from 210,000 unique IP addresses through the Vicuna demo and Chatbot Arena between April and August 2023. Each record includes a conversation ... | huggingface | lmsys/lmsys-chat-1m |
Summarize the dataset metadata into a concise training-data description for supervised fine-tuning. | Name: ShareGPT_Vicuna_unfiltered
Source: huggingface
Dataset ID: anon8231489123/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. Two choices are mentioned: one version removes i... | ShareGPT_Vicuna_unfiltered is an English-language Hugging Face dataset intended for conversational model training and cleaning workflows. It contains a cleaned ShareGPT/Vicuna-style corpus, with variants that either remove or keep instances of the phrase "I'm sorry, but." The dataset is tagged with Apache-2.0 license a... | huggingface | anon8231489123/ShareGPT_Vicuna_unfiltered |
Summarize the dataset metadata into a concise training-data description for supervised fine-tuning. | Name: PhysicalAI-Autonomous-Vehicles
Source: huggingface
Dataset ID: nvidia/PhysicalAI-Autonomous-Vehicles
Description: PHYSICAL AI AUTONOMOUS VEHICLES. The dataset provides one of the largest geographically diverse collections of multi-sensor data for autonomous vehicle researchers building next-generation Physical AI... | PhysicalAI-Autonomous-Vehicles is a large-scale Hugging Face dataset from NVIDIA for autonomous driving and Physical AI research. It includes geographically diverse multi-sensor driving data, collected and labeled through automatic sensor-based processes, totaling about 1700 hours of driving. The dataset is intended fo... | huggingface | nvidia/PhysicalAI-Autonomous-Vehicles |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, scale, languages, format, license, and notable characteristics. | 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.
Tags: task_categories:text-generation; many language tags; license:odc-by; size_ca... | finepdfs is a large-scale Hugging Face dataset built exclusively from PDF sources. It contains roughly 3 trillion tokens spanning about 475 million documents across 1733 languages, making it a highly multilingual corpus for text generation and language model pretraining or fine-tuning. The dataset is distributed in Par... | huggingface | HuggingFaceFW/finepdfs |
Summarize the dataset for supervised fine-tuning use, highlighting domain coverage, scale, format, license, and intended training purpose. | Name: OpenThoughts-114k
Description: Open synthetic reasoning dataset with 114k high-quality examples covering math, science, code, and puzzles. Default subset contains ready-to-train data used to finetune the OpenThinker-7B and OpenThinker-32B models.
Tags: license:apache-2.0; size_categories:100K<n<1M; format:parquet... | OpenThoughts-114k is a synthetic reasoning dataset on Hugging Face with approximately 114,000 high-quality training examples. It covers multiple reasoning-heavy domains, including math, science, code, and puzzles. The default subset is ready to train and was used to fine-tune the OpenThinker-7B and OpenThinker-32B mode... | huggingface | open-thoughts/OpenThoughts-114k |
Summarize the dataset for supervised fine-tuning use. | Name: OpenHermes-2.5
Source: huggingface
Dataset ID: teknium/OpenHermes-2.5
Description: This is the dataset that made OpenHermes 2.5 and Nous Hermes 2 series of models. It is described as the exact compilation and curation of many open source datasets and custom created synthetic datasets underpinning Open Hermes 2/2.... | OpenHermes-2.5 is a large English text dataset on Hugging Face designed for instruction tuning and model distillation. It is a compilation of open-source and synthetic data used to train the OpenHermes 2.5 and Nous Hermes 2 model series. The dataset is distributed in JSON format, tagged as synthetic and GPT-4/distillat... | huggingface | teknium/OpenHermes-2.5 |
Summarize the dataset for supervised fine-tuning use. | Name: alpaca-cleaned
Source: huggingface
Dataset 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, ... | 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 correct known issues such as hallucination-inducing prompts that depended on internet-based information. The dataset supports text generation tasks, is provide... | huggingface | yahma/alpaca-cleaned |
Summarize the dataset metadata into a concise structured description for machine learning use. | {"source":"huggingface","id":"cais/hle","name":"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. Note: ... | {"dataset_name":"hle","full_id":"cais/hle","platform":"Hugging Face","summary":"Humanity's Last Exam is a multimodal benchmark covering broad academic subjects with 2,500 closed-ended questions at the frontier of human knowledge.","modalities":["image","text"],"format":"parquet","license":"mit","size_category":"1K<n<10... | huggingface | cais/hle |
Summarize the dataset metadata into a concise structured description for machine learning use. | {"source":"huggingface","id":"HuggingFaceFW/fineweb-2","name":"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 ODC-By 1.0 license, and validated through extensive ablation ex... | {"dataset_name":"fineweb-2","full_id":"HuggingFaceFW/fineweb-2","platform":"Hugging Face","summary":"FineWeb2 is a large-scale multilingual pretraining dataset covering over 1000 languages, designed for high-quality reproducible text data generation and validated through extensive experiments.","task_categories":["text... | huggingface | HuggingFaceFW/fineweb-2 |
Summarize the dataset and identify its primary machine learning use case. | Name: imagenet-1k
Source: huggingface
Dataset ID: ILSVRC/imagenet-1k
Description: ILSVRC 2012, commonly known as 'ImageNet' is an image dataset organized according to the WordNet hierarchy. Each meaningful concept in WordNet is called a synset. ImageNet aims to provide on average 1000 images to illustrate each synset.
... | ImageNet-1k is a large-scale image dataset from the ILSVRC 2012 benchmark, organized using the WordNet synset hierarchy. It contains images representing many object categories and is widely used for multi-class image classification. The dataset is crowdsourced, English-labeled, image-based, and commonly used for traini... | huggingface | ILSVRC/imagenet-1k |
Summarize the dataset and describe what kind of model training it is intended for. | Name: Alpaca-CoT
Source: huggingface
Dataset ID: QingyiSi/Alpaca-CoT
Description: This repository continuously collects various instruction tuning datasets and standardizes them into the same format, which can be directly loaded by the code of the Alpaca model. It also includes empirical study on various instruction-tu... | Alpaca-CoT is a collection of standardized instruction-tuning datasets designed for direct use with Alpaca-style models. It focuses on instruction-following and chain-of-thought style data, supporting multiple languages including English and Chinese. The dataset is intended for supervised fine-tuning of language models... | huggingface | QingyiSi/Alpaca-CoT |
Summarize the dataset based on its metadata. | Name: PersonaHub
Source: huggingface
ID: proj-persona/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... | PersonaHub is a Hugging Face dataset focused on large-scale synthetic data creation through persona-driven generation. It is associated with the paper "Scaling Synthetic Data Creation with 1,000,000,000 Personas" and introduces a collection of 1 billion diverse personas curated from web data to support varied LLM persp... | huggingface | proj-persona/PersonaHub |
SoloAI SFT Dataset: 20260427-0137
📊 数据集概览
| 属性 | 值 |
|---|---|
| 数据条数 | 30 条 |
| 数据源 | huggingface |
| 生成时间 | 2026-04-27 01:37 |
| 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 LLM practitioners, including what it is, likely use cases, scale, license, and notable characteristics.', 'input': '{"source":"huggingface","id":"fka/prompts.chat","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_categories:text-generation","license:cc0-1.0","size_categories:1K<n<10K","format:csv","modality:text","library:datasets","library:pandas","library:polars","library:mlcroissant","region:us","ChatGPT","prompts","AI","GPT","Claude","Gemini","Llama","Mistral","LLM","prompt-engineering","conversational-ai","text-generation","chatbot","awesome-list"],"downloads":50433,"likes":9680,"created_at":""}', 'output': 'prompts.chat is a community prompt dataset mirrored from the prompts.chat platform and associated Awesome ChatGPT Prompts collection. It focuses on user-shared prompts for systems such as ChatGPT, Claude, Gemini, Llama, and Mistral. The dataset is relatively small, in the 1K to 10K range, stored as CSV text data, and licensed under CC0-1.0, which makes it highly permissive for reuse. Likely use cases include prompt engineering research, prompt retrieval, benchmarking prompt patterns, chatbot prompt libraries, and studying instruction phrasing. A notable characteristic is that it is not primarily a corpus of model conversations or supervised response pairs, but rather a curated collection of prompts from a social platform.', 'source': 'huggingface', 'original_id': 'fka/prompts.chat'}
🤖 数据来源
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- 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
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|---|---|---|
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📈 更新日志
| 版本 | 日期 | 说明 |
|---|---|---|
| v1.0 | 2026-04-27 01:37 | 初始发布，30 条数据 |
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