Introducing Llama 3.1
Llama 3.1 demonstrates state-of-the-art performance on a wide range of industry benchmarks and offers new capabilities, including a 128K context length, improved reasoning supported by eight languages, and Llama 3.1 405B—the largest publicly available foundation model.
Benefits
Meet Llama
For over the past decade, Meta has been focused on putting tools into the hands of developers, and fostering collaboration and advancements among developers, researchers, and organizations. Llama models are available in a range of parameter sizes, enabling developers to select the model that best fits their needs and inference budget. Llama models in Amazon Bedrock open up a world of possibilities because developers don't need to worry about scalability or managing infrastructure. Amazon Bedrock is a very simple turnkey way for developers to get started using Llama.
Use cases
Llama models excel at language nuances, contextual understanding, and complex tasks like translation and dialogue generation, and can handle multi-step tasks effortlessly. Some examples of use cases that Llama models excel at include text summarization and accuracy, text classification, sentiment analysis and nuance reasoning, language modeling, dialog systems, code generation, and following instructions.
Model versions
Meta Llama 3.1 8B
Ideal for limited computational power and resources, faster training times, and edge devices.
Max tokens: 128K
Languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
Fine-tuning supported: Coming soon
Supported use cases: Text summarization, text classification, sentiment analysis, and language translation.
Meta Llama 3.1 70B
Ideal for content creation, conversational AI, language understanding, research development, and enterprise applications.
Max tokens: 128K
Languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
Fine-tuning supported: Coming soon
Supported use cases: Text summarization, text classification, sentiment analysis, and language translation.
Meta Llama 3.1 405B
Ideal for enterprise level applications, research and development, synthetic data generation and model distillation.
Max tokens: 128K
Languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
Fine-tuning supported: Coming soon
Supported use cases: General knowledge, long-form text generation, machine translation, enhanced contextual understanding, advanced reasoning and decision making, better handling of ambiguity and uncertainty, increased creativity and diversity, steerability, math, tool use, multilingual translation, and coding.
Meta Llama 3 8B
Ideal for limited computational power and resources, faster training times, and edge devices.
Max tokens: 8K
Languages: English
Fine-tuning supported: No
Supported use cases: Text summarization, text classification, sentiment analysis, and language translation
Meta Llama 3 70B
Ideal for content creation, conversational AI, language understanding, research development, and enterprise applications.
Max tokens: 8K
Languages: English
Fine-tuning supported: No
Supported use cases: Text summarization and accuracy, text classification and nuance, sentiment analysis and nuance reasoning, language modeling, dialogue systems, code generation, and following instructions.
Meta Llama 2 13B
Fine-tuned model in the parameter size of 13B. Suitable for smaller-scale tasks such as text classification, sentiment analysis, and language translation.
Max tokens: 4K
Languages: English
Fine-tuning supported: Yes
Supported use cases: Assistant-like chat
Meta Llama 2 70B
Fine-tuned model in the parameter size of 70B. Suitable for larger-scale tasks such as language modeling, text generation, and dialogue systems.
Max tokens: 4K
Languages: English
Fine-tuning supported: Yes
Supported use cases: Assistant-like chat
Nomura uses Llama models from Meta in Amazon Bedrock to democratize generative AI
Aniruddh Singh, Nomura's Executive Director and Enterprise Architect, outlines the financial institution’s journey to democratize generative AI firm-wide using Amazon Bedrock and Llama models from Meta. Amazon Bedrock provides critical access to leading foundation models like Llama, enabling seamless integration. Llama offers key benefits to Nomura, including faster innovation, transparency, bias guardrails, and robust performance across text summarization, code generation, log analysis, and document processing.
TaskUs revolutionizes customer experiences using Llama models from Meta in Amazon Bedrock
TaskUs, a leading provider of outsourced digital services and next-generation customer experience to the world’s most innovative companies, helps its clients represent, protect, and grow their brands. Its innovative TaskGPT platform, powered by Amazon Bedrock and Llama models from Meta, empowers teammates to deliver exceptional service. TaskUs builds tools on TaskGPT that leverage Amazon Bedrock and Llama for cost-effective paraphrasing, content generation, comprehension, and complex task handling.