What is Large Language Model (LLM) Data? Uses, Types & Data Examples
What is Large Language Model (LLM) Data?
Large Language Model (LLM) data refers to a collection of textual and visual information used to train advanced language models. LLM data is essential for developing language models capable of understanding human language and generating text or images. This data includes books, images, articles, websites, and conversational transcripts. Examples of LLM data encompass text collections, annotated sentences, and large-scale multilingual data. On this page, you’ll find the best data sources for various types of Large Language Model (LLM) data.
Best Large Language Model (LLM) Datasets & APIs
Nexdata | Foundation Model Data Collection and Data Annotation | Large Language Model(LLM) Data | SFT Data| Red Teaming Services
by
Nexdata
Available for 121 countries
50 TB of text data
5 years of historical data
98% accuracy
Starts at
$5,000 / purchase
Free sample preview
800,000 SFX Professional Sound Effects | Human Metadata | Ideal for Large Language Model (LLM) Data | Soundsnap
by
Soundsnap
Available for 247 countries
800K audio files
10 years of historical data
85% 48 kHz 24 bit or better
Starts at
$500,000 / purchase
Free sample preview
FileMarket | 20,000 photos | AI Training Data | Large Language Model (LLM) Data | Machine Learning (ML) Data | Deep Learning (DL) Data |
by
FileMarket
Available for 249 countries
20K photos
95% accuracy
Pricing available upon request
Free sample preview
Nexdata | Large Language Model Data | SFT Data| Pre-training Data| LLM Data|Text AI & ML Training Data | Natural Language Processing (NLP) Data
by
Nexdata
Available for 89 countries
800 TB
5 years of historical data
90% Accuracy
Starts at
$5,000 / purchase
Free sample preview
Music Data for Large Language Models LLM | 50,000 Music Files | Updated Weekly | Royalty Free Music | Pre-cleared for Generative AI
by
Soundsnap
Available for 249 countries
50K music tracks
10 years of historical data
80% instrumental
Starts at
$500,000 / purchase
Free sample preview
High-Quality B2B Contact Data for AI Model Training and Machine Learning
by
RevenueBase
Available for 249 countries
150M Contacts
1 years of historical data
Starts at
$15,000$14,250 / year
Free sample preview
5% Datarade discount
1% revenue share
FileMarket | Telegram Users Geolocation Data with IP & Consent | 50,000 Records | AI, ML, DL & LLM Training Data
by
FileMarket
Available for 249 countries
50K records
Pricing available upon request
Free sample preview
Bitext | AI Training Data | Hybrid Synthetic Data for LLM Finetuning | Custom Training and Evaluation Datasets for Chatbots
by
bitext
Available for 249 countries
9 Languages
100% Utterances Semantically Equivalent
Available Pricing:
One-off purchase
Monthly License
Yearly License
Free sample preview
Nexdata | Multilingual Read Speech Data | 65,000 Hours | Generative AI Audio Data| Speech Recognition Data | Machine Learning (ML) Data
by
Nexdata
Available for 102 countries
65K Hours
5 years of historical data
98% sentence/word
Starts at
$5,000 / purchase
Free sample preview
FileMarket | Telegram Users Global Web Browsing & Activity Data Feed | 50,000 Records | AI, ML, DL & LLM Training Data
by
FileMarket
Available for 249 countries
50K records
Pricing available upon request
Free sample preview
Monetize data on Datarade Marketplace
List your data on our global B2B marketplace to reach 100k monthly buyers
What are Examples of Large Language Model Data?
Examples of LLM data include:
- Books and Literature: Digitized versions of works across various genres.
- News Articles: Articles from newspapers, magazines, and online news platforms covering a wide range of topics.
- Websites: Text from blogs, forums, and social media platforms that provide diverse conversational.
- Scientific Papers: Research papers and journals that offer specialized and technical language data.
What Data Type is Large Language Model Data?
Large Language Model (LLM) data includes various data types essential for AI training:
- Textual Data: This forms the backbone of LLMs. It includes written content like books, articles, websites, and social media posts, as well as numerical data such as vectors, matrices, and tensors.
- Structured Data: Sometimes, models utilize data from structured formats like databases, tables, or CSV files, especially for tasks involving structured text.
- Metadata: Additional information about the text, such as the source, publication date, and author.
- Tokenized Data: Text is broken down into tokens—words, subwords, or characters. These tokens are the basic units for the LLM learning process.
- Training Labels: In supervised learning, labeled data pairs each text piece with a label or category. This helps in tasks like classification, named entity recognition, and sentiment analysis.
What are Large Language Model Use Cases?
LLM use cases include:
- Generative AI: LLMs can create high-quality written content for blogs, social media, and websites, enhancing productivity for writers and marketers.
- Customer Support: Automated chatbots powered by LLMs can provide efficient and accurate responses to customer inquiries, improving user experience and reducing response times.
- Language Translation: LLMs can translate text between languages with high accuracy, making global communication more accessible and efficient.
- Sentiment Analysis: Businesses use LLMs to analyze customer feedback and social media posts to gauge public sentiment and improve their products and services.
Where Can I Get Data for LLM?
Data for training LLMs can be sourced from various places, including digital libraries, academic repositories, and online platforms. Datarade offers a selection of top-tier providers to meet your LLM training data needs. Our marketplace ensures high-quality LLM datasets from the best AI training data sources.
- Overview
- Datasets
- Guide