Key Features of Llama3-8b

Llama3-8b models boast state-of-the-art performance with 8 billion parameters, responsible AI development with trust and safety tools like Llama Guard 2 and Code Shield, decoder-only transformer architecture, training on over 15 trillion tokens from various sources including non-English data, and fine-tuning using supervised fine-tuning, rejection sampling, and preference optimization.

Where to Find More Information and Updates about Llama3?

For more information and updates about Llama3, visit the [Llama3 website](https://ai.meta.com/blog/meta-llama-3/) and subscribe to the newsletter for the latest news from Meta AI.

Now Offering Free Access to Llama3 on Embed!

Q: How to Access Llama3-8b on Embed?

To access Llama3-8b on Embed, navigate to your chatbot's settings section, select the model as 'llama3-8b', and save your settings.

Exciting news: Embed now supports free access to Llama3 models! This means you can take advantage of the cutting-edge capabilities of Llama3-8b without any cost. Here’s everything you need to know:

How to Access Llama3-8b on Embed

Navigate to Chatbot Settings: Go to the settings section of your chatbot page.
Select Llama3-8b Model: In the chat settings, choose the model as “llama3-8b”.
Save Your Settings: Remember to save your settings to apply the changes.

Embed Settings

Introducing Llama3-8b

Meta has introduced Llama3-8b, the latest generation of their state-of-the-art open source large language model. Here’s what you need to know:

Responsible AI: Meta is committed to developing Llama3 in a responsible manner, offering trust and safety tools like Llama Guard 2 and Code Shield.
Future Developments: Expect new capabilities, longer context windows, additional model sizes, and enhanced performance in future updates.
State-of-the-Art Performance: Llama3-8b models boast state-of-the-art performance with 8 billion parameters, surpassing previous models like Llama2.
Model Architecture: Llama3-8b utilizes a decoder-only transformer architecture with improvements in tokenization efficiency and inference efficiency.
Training Data: Pretrained on over 15 trillion tokens from publicly available sources, including high-quality non-English data covering over 30 languages.
Instruction Fine-Tuning: Llama3-8b models are fine-tuned using a combination of supervised fine-tuning, rejection sampling, and preference optimization to improve model quality.

llama3 performance

What’s Next for Llama3?

Meta plans to release multiple models with new capabilities including multimodality, multilingual conversation, longer context windows, and stronger overall performance. Stay tuned for detailed research papers and updates on future releases!

With free access to Llama3 on Embed, developers can unlock the potential of state-of-the-art language models without any cost. Try it out today and unleash the power of AI in your projects!

For more information and updates, visit the Llama3 website and subscribe to the newsletter for the latest news from Meta AI.