Generative AI foundation models in SageMaker Canvas

Amazon Titan

Amazon Titan is a powerful, general-purpose language model that you can use for tasks such as summarization, text generation (such as creating a blog post), classification, open-ended Q&A, and information extraction. It is pretrained on large datasets, making it suitable for complex tasks and reasoning. To continue supporting best practices in the responsible use of AI, Amazon Titan foundation models are built to detect and remove harmful content in the data, reject inappropriate content in the user input, and filter model outputs that contain inappropriate content (such as hate speech, profanity, and violence).

Anthropic Claude Instant

Anthropic's Claude Instant is a faster and more cost-effective yet still very capable model. This model can handle a range of tasks including casual dialogue, text analysis, summarization, and document question answering. Just like Claude-2, Claude Instant can support up to 100,000 tokens in each prompt, equivalent to about 200 pages of information.

Anthropic Claude-2

Claude-2 is Anthropic's most powerful model, which excels at a wide range of tasks from sophisticated dialogue and creative content generation to detailed instruction following. Claude-2 can take up to 100,000 tokens in each prompt, equivalent to about 200 pages of information. It can generate longer responses compared to its prior version. It supports use cases such as question answering, information extraction, removing PII, content generation, multiple-choice classification, roleplay, comparing text, summarization, and document Q&A with citation.

Falcon-7B-Instruct

Falcon-7B-Instruct has 7 billion parameters and was fine-tuned on a mixture of chat and instruct datasets. It is suitable as a virtual assistant and performs best when following instructions or engaging in conversation. Since the model was trained on large amounts of English-language web data, it carries the stereotypes and biases commonly found online and is not suitable for languages other than English. Compared to Falcon-40B-Instruct, Falcon-7B-Instruct is a slightly smaller and more compact model.

Falcon-40B-Instruct

Falcon-40B-Instruct has 40 billion parameters and was fine-tuned on a mixture of chat and instruct datasets. It is suitable as a virtual assistant and performs best when following instructions or engaging in conversation. Since the model was trained on large amounts of English-language web data, it carries the stereotypes and biases commonly found online and is not suitable for languages other than English. Compared to Falcon-7B-Instruct, Falcon-40B-Instruct is a slightly larger and more powerful model.

Jurassic-2 Mid

Jurassic-2 Mid is a high-performance text generation model trained on a massive corpus of text (current up to mid 2022). It is highly versatile, general-purpose, and capable of composing human-like text and solving complex tasks such as question answering, text classification, and many others. This model offers zero-shot instruction capabilities, allowing it to be directed with only natural language and without the use of examples. It performs up to 30% faster than its predecessor, the Jurassic-1 model.

Jurassic-2 Mid is AI21’s mid-sized model, carefully designed to strike the right balance between exceptional quality and affordability.

Jurassic-2 Ultra

Jurassic-2 Ultra is a high-performance text generation model trained on a massive corpus of text (current up to mid 2022). It is highly versatile, general-purpose, and capable of composing human-like text and solving complex tasks such as question answering, text classification, and many others. This model offers zero-shot instruction capabilities, allowing it to be directed with only natural language and without the use of examples. It performs up to 30% faster than its predecessor, the Jurassic-1 model.

Compared to Jurassic-2 Mid, Jurassic-2 Ultra is a slightly larger and more powerful model.

Llama-2-7b-Chat

Llama-2-7b-Chat is a foundation model by Meta that is suitable for engaging in meaningful and coherent conversations, generating new content, and extracting answers from existing notes. Since the model was trained on large amounts of English-language internet data, it carries the biases and limitations commonly found online and is best-suited for tasks in English.

Llama-2-13B-Chat

Llama-2-13B-Chat by Meta was fine-tuned on conversational data after initial training on internet data. It is optimized for natural dialog and engaging chat abilities, making it well-suited as a conversational agent. Compared to the smaller Llama-2-7b-Chat, Llama-2-13B-Chat has nearly twice as many parameters, allowing it to remember more context and produce more nuanced conversational responses. Like Llama-2-7b-Chat, Llama-2-13B-Chat was trained on English-language data and is best-suited for tasks in English.

Llama-2-70B-Chat

Like Llama-2-7b-Chat and Llama-2-13B-Chat, the Llama-2-70B-Chat model by Meta is optimized for engaging in natural and meaningful dialog. With 70 billion parameters, this large conversational model can remember more extensive context and produce highly coherent responses when compared to the more compact model versions. However, this comes at the cost of slower responses and higher resource requirements. Llama-2-70B-Chat was trained on large amounts of English-language internet data and is best-suited for tasks in English.

Mistral-7B

Mistral-7B by Mistral.AI is an excellent general purpose language model suitable for a wide range of natural language (NLP) tasks like text generation, summarization, and question answering. It utilizes grouped-query attention (GQA) which allows for faster inference speeds, making it perform comparably to models with twice or three times as many parameters. It was trained on a mixture of text data including books, websites, and scientific papers in the English language, so it is best-suited for tasks in English.

Mistral-7B-Chat

Mistral-7B-Chat is a conversational model by Mistral.AI based on Mistral-7B. While Mistral-7B is best for general NLP tasks, Mistral-7B-Chat has been further fine-tuned on conversational data to optimize its abilities for natural, engaging chat. As a result, Mistral-7B-Chat generates more human-like responses and remembers the context of previous responses. Like Mistral-7B, this model is best-suited for English language tasks.

MPT-7B-Instruct

MPT-7B-Instruct is a model for long-form instruction following tasks and can assist you with writing tasks including text summarization and question-answering to save you time and effort. This model was trained on large amounts of fine-tuned data and can handle larger inputs, such as complex documents. Use this model when you want to process large bodies of text or want the model to generate long responses.