instruction stringlengths 53 143 | input stringlengths 310 1.06k | output stringlengths 347 923 | source stringclasses 1
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Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- 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. It is an open-source platform where users can share, discover, and collect AI prompts from the commun... | prompts.chat is a Hugging Face mirror of the Awesome ChatGPT Prompts community repository, focused on collecting and sharing AI prompts. It is best suited for prompt engineering research, prompt discovery, conversational AI experimentation, and text-generation or question-answering prompt libraries rather than raw pret... | huggingface | fka/prompts.chat |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- 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 18.5 trillion tokens. The processing pipeline is optimized for LLM performance and built with the dat... | FineWeb is a massive English web-text corpus derived from CommonCrawl and optimized for large language model training through cleaning and deduplication. With over 18.5 trillion tokens, it is primarily intended for large-scale pretraining and text-generation research rather than conventional instruction tuning. The dat... | huggingface | HuggingFaceFW/fineweb |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- Source: huggingface
- ID: Anthropic/hh-rlhf
- Name: hh-rlhf
- Description: This repository provides human preference data about helpfulness and harmlessness from the HH-RLHF work. These data are intended for training preference or reward models for subsequent RLHF training and are not meant for supe... | HH-RLHF is a human feedback dataset centered on helpfulness and harmlessness preferences, created to support reward modeling and reinforcement learning from human feedback. It is not primarily designed for standard supervised fine-tuning of chat assistants, since the repository itself cautions that doing so may produce... | huggingface | Anthropic/hh-rlhf |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- 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. It has been used to generate high-performing model checkpoints.
- Tags: tas... | OpenOrca is a large English instruction dataset built from augmented FLAN-style data and designed to mirror the task distribution discussed in the Orca family of work. It is well suited for supervised fine-tuning of general-purpose assistants because it spans many NLP task categories, including question answering, summ... | huggingface | Open-Orca/OpenOrca |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- 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 more than 10,000 fully annotated con... | OASST1 is a multilingual assistant conversation dataset created through large-scale human generation and annotation. It contains assistant-style dialogue data across 35 languages, along with extensive quality ratings and annotated conversation trees, making it highly valuable for supervised fine-tuning, ranking, multil... | huggingface | OpenAssistant/oasst1 |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"source":"huggingface","id":"openai/gsm8k","name":"gsm8k","description":"GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems created for question answering on basic mathematical problems requiring multi-step reasoning.","tags":["benchmark:official","ben... | {"name":"gsm8k","summary":"English grade-school math word problem dataset for multi-step reasoning and question answering.","domain":"math","modality":"text","languages":["en"],"license":"mit","size_category":"10K<n<100K","format":"parquet","popularity":{"downloads":871250,"likes":1288},"key_tags":["math-word-problems"... | huggingface | openai/gsm8k |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"source":"huggingface","id":"wikimedia/wikipedia","name":"wikipedia","description":"Wikipedia dataset containing cleaned articles of all languages, built from Wikipedia dumps, with one subset per language and cleaned full article text.","tags":["task_categories:text-generation","task_categories:fill-mask","task_ids:la... | {"name":"wikipedia","summary":"Large multilingual corpus of cleaned Wikipedia articles for language modeling and text generation tasks.","domain":"general knowledge","modality":"text","languages":["multilingual"],"license":["cc-by-sa-3.0","gfdl"],"size_category":"10M<n<100M","format":"parquet","popularity":{"downloads"... | huggingface | wikimedia/wikipedia |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"source":"huggingface","id":"gsdf/EasyNegative","name":"EasyNegative","description":"Negative Embedding trained with Counterfeit for use in stable-diffusion-webui embeddings, with uncertain effectiveness on other models.","tags":["license:other","size_categories:n<1K","format:imagefolder","modality:image","library:dat... | {"name":"EasyNegative","summary":"Small image-related negative embedding resource intended for Stable Diffusion workflows.","domain":"image generation","modality":"image","languages":[],"license":"other","size_category":"n<1K","format":"imagefolder","popularity":{"downloads":32189,"likes":1178},"key_tags":["modality:im... | huggingface | gsdf/EasyNegative |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"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:ml... | {"name":"RedPajama-Data-1T","summary":"Large English open-source text corpus designed as a clean-room reproduction of the LLaMA training dataset.","domain":"language modeling","modality":"text","languages":["en"],"license":"unknown","size_category":"1M<n<10M","format":"unknown","popularity":{"downloads":2136,"likes":11... | huggingface | togethercomputer/RedPajama-Data-1T |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"source":"huggingface","id":"FreedomIntelligence/medical-o1-reasoning-SFT","name":"medical-o1-reasoning-SFT","description":"Medical reasoning dataset for supervised fine-tuning, distilled from Deepseek-R1 and built on medical verifiable problems, containing medical SFT data and related updates.","tags":["task_categori... | {"name":"medical-o1-reasoning-SFT","summary":"Bilingual medical reasoning and instruction-tuning dataset for question answering and text generation, focused on verifiable medical problems.","domain":"medical","modality":"text","languages":["en","zh"],"license":"apache-2.0","size_category":"10K<n<100K","format":"json","... | huggingface | FreedomIntelligence/medical-o1-reasoning-SFT |
Summarize the dataset for LLM pretraining use, including its scale, domain, language, license, and notable metadata. | Name: fineweb-edu
Description: FineWeb-Edu is a dataset of 1.3 trillion tokens of educational web data filtered from FineWeb using an educational quality classifier. It is described as high-quality educational web content and references multiple research papers.
Tags: task_categories:text-generation, language:en, licen... | fineweb-edu is a large-scale English educational text dataset intended for text generation and LLM pretraining. It contains about 1.3 trillion tokens of high-quality educational web pages filtered from the FineWeb corpus using an educational quality classifier based on Llama3-70B-Instruct annotations. The dataset is di... | huggingface | HuggingFaceFW/fineweb-edu |
Provide a concise dataset summary emphasizing suitability for language model pretraining, scale, language, and license. | 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: 4058
Likes: 1025 | dolma is an open English-language corpus designed for language model pretraining research. It contains three trillion tokens, making it an extremely large-scale dataset for text generation and language modeling tasks. The dataset is licensed under ODC-BY and is associated with research papers such as arXiv:2402.00159. ... | huggingface | allenai/dolma |
Summarize the dataset with focus on content type, multilingual/code characteristics, licensing, size, and intended use. | Name: the-stack
Description: The Stack is a code dataset initially released with 30 programming languages and permissive licenses, later updated to exclude weak copyleft licenses and expand permissive licenses to 193 total. The near-deduplicated dataset is 3TB in size.
Tags: task_categories:text-generation, language_cr... | the-stack is a large multilingual code dataset created for text generation and code model training. It contains source code across many programming languages and was curated to include permissive licenses while excluding weak copyleft licenses in later versions. The dataset is near-deduplicated and approximately 3TB in... | huggingface | bigcode/the-stack |
Describe the dataset in terms of its generation method, target language simplicity, training use case, and license. | Name: TinyStories
Description: Dataset containing synthetically generated short stories created by GPT-3.5 and GPT-4 using a small vocabulary. It is described in arXiv:2305.07759 and includes training and validation files for model development.
Tags: task_categories:text-generation, language:en, license:cdla-sharing-1.... | TinyStories is an English synthetic text dataset made up of short stories generated by GPT-3.5 and GPT-4 using a constrained small vocabulary. It is designed for text generation research and is especially useful for training and evaluating small language models on simple narrative content. The dataset is distributed in... | huggingface | roneneldan/TinyStories |
Summarize the instruction-tuning dataset, including task types, data origin, size, format, and license. | Name: databricks-dolly-15k
Description: databricks-dolly-15k is an open source dataset of instruction-following records generated by thousands of Databricks employees across categories such as brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization.
Tags: task_categories... | databricks-dolly-15k is an English instruction-following dataset intended for supervised fine-tuning of assistant models. It contains around 15,000 human-generated records created by Databricks employees, covering tasks such as brainstorming, classification, question answering, generation, information extraction, and s... | huggingface | databricks/databricks-dolly-15k |
Summarize the dataset and identify its main use case, modality, language, license, approximate size, and notable popularity signals. | 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 dataset from Hugging Face designed for instruction tuning. It contains about 52,000 instruction-response demonstrations generated with text-davinci-003 and is intended to improve how language models follow user instructions. The dataset is categorized for text generation, uses the CC-BY-NC-4.0... | huggingface | tatsu-lab/alpaca |
Summarize the resource and identify its purpose, modality, language, license, approximate size, relevant usage context, and popularity signals. | 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 described as helpful for generat... | bad_prompt is an English image-related Hugging Face resource associated with Stable Diffusion workflows. It is a negative embedding or textual inversion asset intended to compress a negative prompt into a reusable embedding token, with reported benefits for image generation details such as hands. The resource is licens... | huggingface | Nerfgun3/bad_prompt |
Summarize the dataset and highlight its purpose, scale, language, license, format, and notable characteristics for LLM training. | Dataset name: falcon-refinedweb
Source: huggingface
Dataset ID: tiiuae/falcon-refinedweb
Description: Falcon RefinedWeb is a massive English web dataset built by TII and released under an ODC-By 1.0 license. It is built through stringent filtering and large-scale deduplication of CommonCrawl. Models trained on RefinedW... | Falcon RefinedWeb is a large-scale English web text dataset released on Hugging Face by TII under the ODC-By 1.0 license. It is derived from CommonCrawl using stringent filtering and large-scale deduplication to improve quality. The dataset is intended for text generation and LLM pretraining, with reported model perfor... | huggingface | tiiuae/falcon-refinedweb |
Summarize the dataset and explain what it contains, how it was collected, and why it is useful for LLM research or supervised fine-tuning. | Dataset name: lmsys-chat-1m
Source: huggingface
Dataset ID: lmsys/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 ... | LMSYS-Chat-1M is a large real-world conversation dataset hosted on Hugging Face that contains one million chats involving 25 state-of-the-art language models. The data was collected from live user interactions on the Vicuna demo and Chatbot Arena between April and August 2023, covering traffic from 210,000 unique IP ad... | huggingface | lmsys/lmsys-chat-1m |
Summarize the dataset metadata and key characteristics. | 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. Two choices: removes instances of "I'm sorry, but" or keeps them. Full description available on the dataset page.
Tags: la... | ShareGPT_Vicuna_unfiltered is a Hugging Face dataset focused on English-language data and licensed under Apache-2.0. It appears to be a cleaned and curated version of ShareGPT/Vicuna-style conversations, with variants that either remove or retain instances of the phrase "I'm sorry, but" for training purposes. The datas... | huggingface | anon8231489123/ShareGPT_Vicuna_unfiltered |
Summarize the dataset metadata and key characteristics. | Name: PhysicalAI-Autonomous-Vehicles
Description: PHYSICAL AI AUTONOMOUS VEHICLES. The dataset provides one of the largest, geographically diverse collections of multi-sensor data for AV researchers to build next-generation Physical AI based end-to-end driving systems. It is ready for commercial/non-commercial AV use p... | PhysicalAI-Autonomous-Vehicles is a Hugging Face dataset for autonomous vehicle research. It contains a large and geographically diverse multi-sensor driving dataset intended to support Physical AI and end-to-end driving systems. The data collection and labeling methods are both automatic/sensor-based, and the dataset ... | huggingface | nvidia/PhysicalAI-Autonomous-Vehicles |
Summarize the dataset based on the provided metadata. | Source: huggingface
ID: HuggingFaceFW/finepdfs
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.
Downloads: 21348
Likes: 853
Tags: t... | finepdfs is a large multilingual text-generation dataset on Hugging Face built entirely from PDF sources. It contains approximately 3 trillion tokens spanning 475 million documents across 1733 languages, making it one of the largest publicly available PDF-derived corpora. The dataset is distributed in parquet format, s... | huggingface | HuggingFaceFW/finepdfs |
Summarize the dataset based on the provided metadata. | Source: huggingface
ID: open-thoughts/OpenThoughts-114k
Name: OpenThoughts-114k
Description: Open synthetic reasoning dataset with 114k high-quality examples covering math, science, code, and puzzles. The default subset contains ready-to-train data used to finetune the OpenThinker-7B and OpenThinker-32B models.
Downloa... | OpenThoughts-114k is a synthetic reasoning dataset on Hugging Face containing 114,000 high-quality training examples. It focuses on domains such as math, science, coding, and puzzles, and is designed for supervised fine-tuning of reasoning models. The dataset is provided in parquet format, supports common data tooling ... | huggingface | open-thoughts/OpenThoughts-114k |
Summarize the dataset metadata into a concise SFT-ready description. | 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 described as an exact compilation and curation of many open source datasets and custom created synthetic datasets underpinning the Open Hermes 2/2.5 and... | OpenHermes-2.5 is a large English text dataset on Hugging Face used to train the OpenHermes 2.5 and Nous Hermes 2 model series. It is a JSON-formatted compilation of open-source and synthetic data, tagged with GPT-4, distillation, and compilation, with an estimated size between 1M and 10M examples. The dataset is popul... | huggingface | teknium/OpenHermes-2.5 |
Summarize the dataset metadata into a concise SFT-ready description. | 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 a cleaned English instruction-tuning dataset on Hugging Face derived from the original Stanford Alpaca release. It removes problematic and hallucination-inducing instructions, making it better suited for text generation and instruction-finetuning tasks. The dataset is provided in JSON format, licensed... | huggingface | yahma/alpaca-cleaned |
Summarize the dataset metadata into a concise description for instruction tuning. | Source: huggingface
Dataset 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. The datase... | hle is an official Hugging Face benchmark dataset from cais/hle. It is a multimodal academic evaluation benchmark called Humanity's Last Exam, containing 2,500 closed-ended questions spanning many subjects at the frontier of human knowledge. The dataset includes both image and text modalities, is distributed in parquet... | huggingface | cais/hle |
Summarize the dataset metadata into a concise description for instruction tuning. | Source: huggingface
Dataset 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 described as fully reproducible, extensively validated through hundreds of ablation experiments, and releas... | fineweb-2 is a large-scale multilingual pretraining dataset published on Hugging Face by HuggingFaceFW. It is the second iteration of FineWeb and is designed for text generation and language model pretraining across more than 1000 languages. The dataset is text and tabular in modality, extremely large in scale (tagged ... | huggingface | HuggingFaceFW/fineweb-2 |
Summarize the dataset and extract its key metadata for machine learning use. | Source: huggingface
Dataset ID: ILSVRC/imagenet-1k
Name: imagenet-1k
Description: ILSVRC 2012, commonly known as 'ImageNet', is an image dataset organized according to the WordNet hierarchy. It contains synsets representing meaningful concepts, mostly nouns, and aims to provide around 1000 images per synset. It is wide... | {"summary":"ImageNet-1k is a large-scale image classification dataset from ILSVRC 2012, organized using the WordNet hierarchy. It contains images mapped to synsets and is a standard benchmark for multi-class image classification.","task_category":"image-classification","task_id":"multi-class-image-classification","moda... | huggingface | ILSVRC/imagenet-1k |
Summarize the dataset and extract its key metadata for instruction tuning use. | Source: huggingface
Dataset ID: QingyiSi/Alpaca-CoT
Name: Alpaca-CoT
Description: This repository continuously collects various instruction tuning datasets and standardizes them into a unified format that can be directly loaded by Alpaca model code. It also supports empirical study on instruction-tuning datasets.
Tags:... | {"summary":"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 aggregation for supervised fine-tuning and related experiments.","task_category":"instruction-tuning","keywords":["Inst... | huggingface | QingyiSi/Alpaca-CoT |
Summarize the dataset and highlight its purpose, scale, languages, tasks, and notable metadata. | Dataset 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 l... | PersonaHub is a Hugging Face dataset focused on large-scale synthetic data creation through persona-driven generation. Introduced alongside the paper "Scaling Synthetic Data Creation with 1,000,000,000 Personas," it presents PERSONA HUB, a resource of 1 billion diverse personas automatically curated from web data to he... | huggingface | proj-persona/PersonaHub |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- 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. It is an open-source platform where users can share, discover, and collect AI prompts from the commun... | prompts.chat is a Hugging Face mirror of the Awesome ChatGPT Prompts community repository, focused on collecting and sharing AI prompts. It is best suited for prompt engineering research, prompt discovery, conversational AI experimentation, and text-generation or question-answering prompt libraries rather than raw pret... | huggingface | fka/prompts.chat |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- 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 18.5 trillion tokens. The processing pipeline is optimized for LLM performance and built with the dat... | FineWeb is a massive English web-text corpus derived from CommonCrawl and optimized for large language model training through cleaning and deduplication. With over 18.5 trillion tokens, it is primarily intended for large-scale pretraining and text-generation research rather than conventional instruction tuning. The dat... | huggingface | HuggingFaceFW/fineweb |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- Source: huggingface
- ID: Anthropic/hh-rlhf
- Name: hh-rlhf
- Description: This repository provides human preference data about helpfulness and harmlessness from the HH-RLHF work. These data are intended for training preference or reward models for subsequent RLHF training and are not meant for supe... | HH-RLHF is a human feedback dataset centered on helpfulness and harmlessness preferences, created to support reward modeling and reinforcement learning from human feedback. It is not primarily designed for standard supervised fine-tuning of chat assistants, since the repository itself cautions that doing so may produce... | huggingface | Anthropic/hh-rlhf |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- 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. It has been used to generate high-performing model checkpoints.
- Tags: tas... | OpenOrca is a large English instruction dataset built from augmented FLAN-style data and designed to mirror the task distribution discussed in the Orca family of work. It is well suited for supervised fine-tuning of general-purpose assistants because it spans many NLP task categories, including question answering, summ... | huggingface | Open-Orca/OpenOrca |
Summarize the dataset for supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata. | Dataset metadata:
- 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 more than 10,000 fully annotated con... | OASST1 is a multilingual assistant conversation dataset created through large-scale human generation and annotation. It contains assistant-style dialogue data across 35 languages, along with extensive quality ratings and annotated conversation trees, making it highly valuable for supervised fine-tuning, ranking, multil... | huggingface | OpenAssistant/oasst1 |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"source":"huggingface","id":"openai/gsm8k","name":"gsm8k","description":"GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems created for question answering on basic mathematical problems requiring multi-step reasoning.","tags":["benchmark:official","ben... | {"name":"gsm8k","summary":"English grade-school math word problem dataset for multi-step reasoning and question answering.","domain":"math","modality":"text","languages":["en"],"license":"mit","size_category":"10K<n<100K","format":"parquet","popularity":{"downloads":871250,"likes":1288},"key_tags":["math-word-problems"... | huggingface | openai/gsm8k |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"source":"huggingface","id":"wikimedia/wikipedia","name":"wikipedia","description":"Wikipedia dataset containing cleaned articles of all languages, built from Wikipedia dumps, with one subset per language and cleaned full article text.","tags":["task_categories:text-generation","task_categories:fill-mask","task_ids:la... | {"name":"wikipedia","summary":"Large multilingual corpus of cleaned Wikipedia articles for language modeling and text generation tasks.","domain":"general knowledge","modality":"text","languages":["multilingual"],"license":["cc-by-sa-3.0","gfdl"],"size_category":"10M<n<100M","format":"parquet","popularity":{"downloads"... | huggingface | wikimedia/wikipedia |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"source":"huggingface","id":"gsdf/EasyNegative","name":"EasyNegative","description":"Negative Embedding trained with Counterfeit for use in stable-diffusion-webui embeddings, with uncertain effectiveness on other models.","tags":["license:other","size_categories:n<1K","format:imagefolder","modality:image","library:dat... | {"name":"EasyNegative","summary":"Small image-related negative embedding resource intended for Stable Diffusion workflows.","domain":"image generation","modality":"image","languages":[],"license":"other","size_category":"n<1K","format":"imagefolder","popularity":{"downloads":32189,"likes":1178},"key_tags":["modality:im... | huggingface | gsdf/EasyNegative |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"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:ml... | {"name":"RedPajama-Data-1T","summary":"Large English open-source text corpus designed as a clean-room reproduction of the LLaMA training dataset.","domain":"language modeling","modality":"text","languages":["en"],"license":"unknown","size_category":"1M<n<10M","format":"unknown","popularity":{"downloads":2136,"likes":11... | huggingface | togethercomputer/RedPajama-Data-1T |
Summarize the dataset metadata into a concise description suitable for supervised fine-tuning data preparation. | {"source":"huggingface","id":"FreedomIntelligence/medical-o1-reasoning-SFT","name":"medical-o1-reasoning-SFT","description":"Medical reasoning dataset for supervised fine-tuning, distilled from Deepseek-R1 and built on medical verifiable problems, containing medical SFT data and related updates.","tags":["task_categori... | {"name":"medical-o1-reasoning-SFT","summary":"Bilingual medical reasoning and instruction-tuning dataset for question answering and text generation, focused on verifiable medical problems.","domain":"medical","modality":"text","languages":["en","zh"],"license":"apache-2.0","size_category":"10K<n<100K","format":"json","... | huggingface | FreedomIntelligence/medical-o1-reasoning-SFT |
Summarize the dataset for LLM pretraining use, including its scale, domain, language, license, and notable metadata. | Name: fineweb-edu
Description: FineWeb-Edu is a dataset of 1.3 trillion tokens of educational web data filtered from FineWeb using an educational quality classifier. It is described as high-quality educational web content and references multiple research papers.
Tags: task_categories:text-generation, language:en, licen... | fineweb-edu is a large-scale English educational text dataset intended for text generation and LLM pretraining. It contains about 1.3 trillion tokens of high-quality educational web pages filtered from the FineWeb corpus using an educational quality classifier based on Llama3-70B-Instruct annotations. The dataset is di... | huggingface | HuggingFaceFW/fineweb-edu |
Provide a concise dataset summary emphasizing suitability for language model pretraining, scale, language, and license. | 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: 4058
Likes: 1025 | dolma is an open English-language corpus designed for language model pretraining research. It contains three trillion tokens, making it an extremely large-scale dataset for text generation and language modeling tasks. The dataset is licensed under ODC-BY and is associated with research papers such as arXiv:2402.00159. ... | huggingface | allenai/dolma |
Summarize the dataset with focus on content type, multilingual/code characteristics, licensing, size, and intended use. | Name: the-stack
Description: The Stack is a code dataset initially released with 30 programming languages and permissive licenses, later updated to exclude weak copyleft licenses and expand permissive licenses to 193 total. The near-deduplicated dataset is 3TB in size.
Tags: task_categories:text-generation, language_cr... | the-stack is a large multilingual code dataset created for text generation and code model training. It contains source code across many programming languages and was curated to include permissive licenses while excluding weak copyleft licenses in later versions. The dataset is near-deduplicated and approximately 3TB in... | huggingface | bigcode/the-stack |
Describe the dataset in terms of its generation method, target language simplicity, training use case, and license. | Name: TinyStories
Description: Dataset containing synthetically generated short stories created by GPT-3.5 and GPT-4 using a small vocabulary. It is described in arXiv:2305.07759 and includes training and validation files for model development.
Tags: task_categories:text-generation, language:en, license:cdla-sharing-1.... | TinyStories is an English synthetic text dataset made up of short stories generated by GPT-3.5 and GPT-4 using a constrained small vocabulary. It is designed for text generation research and is especially useful for training and evaluating small language models on simple narrative content. The dataset is distributed in... | huggingface | roneneldan/TinyStories |
Summarize the instruction-tuning dataset, including task types, data origin, size, format, and license. | Name: databricks-dolly-15k
Description: databricks-dolly-15k is an open source dataset of instruction-following records generated by thousands of Databricks employees across categories such as brainstorming, classification, closed QA, generation, information extraction, open QA, and summarization.
Tags: task_categories... | databricks-dolly-15k is an English instruction-following dataset intended for supervised fine-tuning of assistant models. It contains around 15,000 human-generated records created by Databricks employees, covering tasks such as brainstorming, classification, question answering, generation, information extraction, and s... | huggingface | databricks/databricks-dolly-15k |
Summarize the dataset and identify its main use case, modality, language, license, approximate size, and notable popularity signals. | 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 dataset from Hugging Face designed for instruction tuning. It contains about 52,000 instruction-response demonstrations generated with text-davinci-003 and is intended to improve how language models follow user instructions. The dataset is categorized for text generation, uses the CC-BY-NC-4.0... | huggingface | tatsu-lab/alpaca |
Summarize the resource and identify its purpose, modality, language, license, approximate size, relevant usage context, and popularity signals. | 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 described as helpful for generat... | bad_prompt is an English image-related Hugging Face resource associated with Stable Diffusion workflows. It is a negative embedding or textual inversion asset intended to compress a negative prompt into a reusable embedding token, with reported benefits for image generation details such as hands. The resource is licens... | huggingface | Nerfgun3/bad_prompt |
Summarize the dataset and highlight its purpose, scale, language, license, format, and notable characteristics for LLM training. | Dataset name: falcon-refinedweb
Source: huggingface
Dataset ID: tiiuae/falcon-refinedweb
Description: Falcon RefinedWeb is a massive English web dataset built by TII and released under an ODC-By 1.0 license. It is built through stringent filtering and large-scale deduplication of CommonCrawl. Models trained on RefinedW... | Falcon RefinedWeb is a large-scale English web text dataset released on Hugging Face by TII under the ODC-By 1.0 license. It is derived from CommonCrawl using stringent filtering and large-scale deduplication to improve quality. The dataset is intended for text generation and LLM pretraining, with reported model perfor... | huggingface | tiiuae/falcon-refinedweb |
Summarize the dataset and explain what it contains, how it was collected, and why it is useful for LLM research or supervised fine-tuning. | Dataset name: lmsys-chat-1m
Source: huggingface
Dataset ID: lmsys/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 ... | LMSYS-Chat-1M is a large real-world conversation dataset hosted on Hugging Face that contains one million chats involving 25 state-of-the-art language models. The data was collected from live user interactions on the Vicuna demo and Chatbot Arena between April and August 2023, covering traffic from 210,000 unique IP ad... | huggingface | lmsys/lmsys-chat-1m |
Summarize the dataset metadata and key characteristics. | 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. Two choices: removes instances of "I'm sorry, but" or keeps them. Full description available on the dataset page.
Tags: la... | ShareGPT_Vicuna_unfiltered is a Hugging Face dataset focused on English-language data and licensed under Apache-2.0. It appears to be a cleaned and curated version of ShareGPT/Vicuna-style conversations, with variants that either remove or retain instances of the phrase "I'm sorry, but" for training purposes. The datas... | huggingface | anon8231489123/ShareGPT_Vicuna_unfiltered |
Summarize the dataset metadata and key characteristics. | Name: PhysicalAI-Autonomous-Vehicles
Description: PHYSICAL AI AUTONOMOUS VEHICLES. The dataset provides one of the largest, geographically diverse collections of multi-sensor data for AV researchers to build next-generation Physical AI based end-to-end driving systems. It is ready for commercial/non-commercial AV use p... | PhysicalAI-Autonomous-Vehicles is a Hugging Face dataset for autonomous vehicle research. It contains a large and geographically diverse multi-sensor driving dataset intended to support Physical AI and end-to-end driving systems. The data collection and labeling methods are both automatic/sensor-based, and the dataset ... | huggingface | nvidia/PhysicalAI-Autonomous-Vehicles |
Summarize the dataset based on the provided metadata. | Source: huggingface
ID: HuggingFaceFW/finepdfs
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.
Downloads: 21348
Likes: 853
Tags: t... | finepdfs is a large multilingual text-generation dataset on Hugging Face built entirely from PDF sources. It contains approximately 3 trillion tokens spanning 475 million documents across 1733 languages, making it one of the largest publicly available PDF-derived corpora. The dataset is distributed in parquet format, s... | huggingface | HuggingFaceFW/finepdfs |
Summarize the dataset based on the provided metadata. | Source: huggingface
ID: open-thoughts/OpenThoughts-114k
Name: OpenThoughts-114k
Description: Open synthetic reasoning dataset with 114k high-quality examples covering math, science, code, and puzzles. The default subset contains ready-to-train data used to finetune the OpenThinker-7B and OpenThinker-32B models.
Downloa... | OpenThoughts-114k is a synthetic reasoning dataset on Hugging Face containing 114,000 high-quality training examples. It focuses on domains such as math, science, coding, and puzzles, and is designed for supervised fine-tuning of reasoning models. The dataset is provided in parquet format, supports common data tooling ... | huggingface | open-thoughts/OpenThoughts-114k |
Summarize the dataset metadata into a concise SFT-ready description. | 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 described as an exact compilation and curation of many open source datasets and custom created synthetic datasets underpinning the Open Hermes 2/2.5 and... | OpenHermes-2.5 is a large English text dataset on Hugging Face used to train the OpenHermes 2.5 and Nous Hermes 2 model series. It is a JSON-formatted compilation of open-source and synthetic data, tagged with GPT-4, distillation, and compilation, with an estimated size between 1M and 10M examples. The dataset is popul... | huggingface | teknium/OpenHermes-2.5 |
Summarize the dataset metadata into a concise SFT-ready description. | 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 a cleaned English instruction-tuning dataset on Hugging Face derived from the original Stanford Alpaca release. It removes problematic and hallucination-inducing instructions, making it better suited for text generation and instruction-finetuning tasks. The dataset is provided in JSON format, licensed... | huggingface | yahma/alpaca-cleaned |
Summarize the dataset metadata into a concise description for instruction tuning. | Source: huggingface
Dataset 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. The datase... | hle is an official Hugging Face benchmark dataset from cais/hle. It is a multimodal academic evaluation benchmark called Humanity's Last Exam, containing 2,500 closed-ended questions spanning many subjects at the frontier of human knowledge. The dataset includes both image and text modalities, is distributed in parquet... | huggingface | cais/hle |
Summarize the dataset metadata into a concise description for instruction tuning. | Source: huggingface
Dataset 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 described as fully reproducible, extensively validated through hundreds of ablation experiments, and releas... | fineweb-2 is a large-scale multilingual pretraining dataset published on Hugging Face by HuggingFaceFW. It is the second iteration of FineWeb and is designed for text generation and language model pretraining across more than 1000 languages. The dataset is text and tabular in modality, extremely large in scale (tagged ... | huggingface | HuggingFaceFW/fineweb-2 |
Summarize the dataset and extract its key metadata for machine learning use. | Source: huggingface
Dataset ID: ILSVRC/imagenet-1k
Name: imagenet-1k
Description: ILSVRC 2012, commonly known as 'ImageNet', is an image dataset organized according to the WordNet hierarchy. It contains synsets representing meaningful concepts, mostly nouns, and aims to provide around 1000 images per synset. It is wide... | {"summary":"ImageNet-1k is a large-scale image classification dataset from ILSVRC 2012, organized using the WordNet hierarchy. It contains images mapped to synsets and is a standard benchmark for multi-class image classification.","task_category":"image-classification","task_id":"multi-class-image-classification","moda... | huggingface | ILSVRC/imagenet-1k |
Summarize the dataset and extract its key metadata for instruction tuning use. | Source: huggingface
Dataset ID: QingyiSi/Alpaca-CoT
Name: Alpaca-CoT
Description: This repository continuously collects various instruction tuning datasets and standardizes them into a unified format that can be directly loaded by Alpaca model code. It also supports empirical study on instruction-tuning datasets.
Tags:... | {"summary":"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 aggregation for supervised fine-tuning and related experiments.","task_category":"instruction-tuning","keywords":["Inst... | huggingface | QingyiSi/Alpaca-CoT |
Summarize the dataset and highlight its purpose, scale, languages, tasks, and notable metadata. | Dataset 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 l... | PersonaHub is a Hugging Face dataset focused on large-scale synthetic data creation through persona-driven generation. Introduced alongside the paper "Scaling Synthetic Data Creation with 1,000,000,000 Personas," it presents PERSONA HUB, a resource of 1 billion diverse personas automatically curated from web data to he... | huggingface | proj-persona/PersonaHub |
SoloAI SFT Dataset: 20260502-0137
📊 数据集概览
| 属性 | 值 |
|---|---|
| 数据条数 | 30 条 |
| 数据源 | huggingface |
| 生成时间 | 2026-05-02 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 supervised fine-tuning use, highlighting what it contains, typical use cases, and notable metadata.', 'input': 'Dataset metadata:\n- Source: huggingface\n- ID: fka/prompts.chat\n- Name: prompts.chat\n- Description: a.k.a. Awesome ChatGPT Prompts. This is a Dataset Repository mirror of prompts.chat — a social platform for AI prompts. It is an open-source platform where users can share, discover, and collect AI prompts from the community.\n- 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\n- Downloads: 60033\n- Likes: 9680\n- Created at: ', 'output': 'prompts.chat is a Hugging Face mirror of the Awesome ChatGPT Prompts community repository, focused on collecting and sharing AI prompts. It is best suited for prompt engineering research, prompt discovery, conversational AI experimentation, and text-generation or question-answering prompt libraries rather than raw pretraining. The dataset is relatively small (1K to 10K examples), stored in CSV format, and licensed under CC0-1.0, making it highly reusable. Its tags indicate broad relevance across major LLM ecosystems such as ChatGPT, Claude, Gemini, Llama, and Mistral. Strong community engagement is reflected in its high download and like counts.', '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:
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- 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
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💰 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 | 2026-05-02 01:37 | 初始发布，30 条数据 |
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