Benefits
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Broad range of applications
Generate natural language text for a broad range of tasks such as summarization, content creation, and question answering.
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Deliver relevant search results
Enhance search accuracy and improve personalized recommendations.
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Built-in support for responsible AI
Support responsible use of AI by reducing inappropriate or harmful content.
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Easy customization
Fine-tune Amazon Titan models with your own data to customize the model and perform organization specific tasks.
Benefits
-
Broad range of applications
Generate natural language text for a broad range of tasks such as summarization, content creation, and question answering.
-
Deliver relevant search results
Enhance search accuracy and improve personalized recommendations.
-
Built-in support for responsible AI
Support responsible use of AI by reducing inappropriate or harmful content.
-
Easy customization
Fine-tune Amazon Titan models with your own data to customize the model and perform organization specific tasks.
Meet Amazon Titan
Amazon Titan FMs are a family of FMs pretrained by AWS on large datasets, making them powerful, general purpose models built to support a variety of use cases. Use them as is or privately customize them with your own data.
Use Cases
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Text generation
Use Titan Text for creating copy for blog posts and web pages, classifying articles into categories, open-ended Q&A, and information extraction.
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Summarization
Get the gist of lengthy documents of text, such as reports and event books, with summaries based on natural language prompts.
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Semantic search
Use Titan Embeddings for applications like personalization and search. By comparing embeddings, the model can produce more relevant and contextual responses than word matching.
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Retrieval augmented generation
Deliver more up-to-date and accurate results for user queries by connecting FMs to your data sources.
Use Cases
-
Text generation
Use Titan Text for creating copy for blog posts and web pages, classifying articles into categories, open-ended Q&A, and information extraction.
-
Summarization
Get the gist of lengthy documents of text, such as reports and event books, with summaries based on natural language prompts.
-
Semantic search
Use Titan Embeddings for applications like personalization and search. By comparing embeddings, the model can produce more relevant and contextual responses than word matching.
-
Retrieval augmented generation
Deliver more up-to-date and accurate results for user queries by connecting FMs to your data sources.
Model versions
Titan Text Express (preview)
A large language model offering a balance of price and performance.
Max tokens: 8K
Languages: 100+ languages
Supported use cases: Retrieval augmented generation, open ended text generation, brainstorming, summarization, code generation, table creation, data formatting, paraphrasing, chain of thought, rewrite, extraction, Q&A, chat.
Titan Text Lite (preview)
Affordable and compact, ideal for basic tasks and fine-tuning.
Max tokens: 4K
Languages: English
Supported use cases: Open ended text generation, brainstorming, summarization, code generation, table creation, data formatting, paraphrasing, chain of thought, rewrite, extraction, Q&A, chat.
Titan Embeddings (generally available)
Large language model that translates text into a numerical representation.
Max tokens: 8K
Languages: 25+ languages
Embeddings: 1,536
Supported use cases: Text retrieval, semantic similarity, clustering.