On July 23, 2024, Meta released a new version of the Llama model, named Llama 3.1, Meta’s most advanced large-scale language model to date.
Here’s a summary of the key points:
Youtube Video
1. Introduction of LLaMA 3.1:
Meta releases LLaMA 3.1, highlighting its advanced capabilities compared to previous versions. LLaMa 3.1 features three models: 405B, 70B, and 8B, with 405B being the most powerful and versatile of these.
To train this new Llama 3.1 405B model, over 15 trillion tokens were used with a standard transformer model architecture with decoder instead of a mixed expert model.
2. Improvements and features:
Details improvements in accuracy, efficiency, and natural language understanding capabilities.
Picture of: https://ai.meta.com/blog/meta-llama-3-1/
Improvements:
Context length expansion to 128K.
Improvements in data quality and quantity in pre- and post-training.
Computing requirements reduced from 16-bit (BF16) to 8-bit (FP8) to achieve large-scale inference with the 405B model.
Features:
Real-time and batch inference
Supervised fine-tuning
Model evaluation for your specific application
Continuous pre-training
Recall Augmented Generation (RAG)
Function calling
Synthetic data generation
3. Practical Applications:
LLaMA 3.1 is designed to be used in a variety of applications, from chatbots to data analysis.
From day one, the collection of Llama 3.1 models can be used in services such as AWS, Azure, Databricks, Snowflake, among others.
Picture of: https://ai.meta.com/blog/meta-llama-3-1/
4. Accessibility:
Meta highlights its commitment to making LLaMA 3.1 accessible to researchers and developers.
Llama can be downloaded and fully customized to developers’ needs and applications, as well as trained with new datasets.
Open source applications such as Llama Guard 3, a multilingual security model, and Prompt Guard, a prompt injection filter.
And Llama Stack a set of standardized, opinion-based interfaces on how to build canonical components of the toolkit.
Conclusion
Llama 3.1 promises to transform how businesses and developers interact with language models, making it easier to build applications that harness the power of artificial intelligence, doing the heavy lifting of training the model with large amounts of data, and opening the door to constant innovation.
References:
https://ai.meta.com/blog/meta-llama-3-1/
https://about.fb.com/news/2024/07/open-source-ai-is-the-path-forward/
