What is Flame 2? Meta and Microsoft present the next generation

If you love AI technology, then you must have heard of Llama 2. In this article, you can explore Llama 2 and we have given you information on where you can get it. For that, you need to read the article for more details and information. Follow us for all the latest ideas and updates on PKB News.

What is Flame 2?

As we all know, the open source AI model puts an emphasis on responsibility. Meta and Microsoft have teamed up to introduce Llama 2, which is a big, basically generalized, next-generation language. The AI ​​model is for commercial and research purposes. The updated open source code places a much greater emphasis on responsibility. The Llama 2 is a language model that Meta released today and so people are very excited to fully support the release with full integration into Hugging Face. Llama 2 is released with a very permissive community license and is widely available for commercial use. The code, models and adjusted models will be released today.

A collaboration with Meta has occurred to ensure a smooth integration into the Hugging Face ecosystem. You can find the 12 open access and 3 precision models with the organic Meta checkpoints, also their corresponding models in the Hub. Among the features and other integrations that are being released, we have:

  • models in the center
  • Integration of transformers
  • Text generation inference
  • Integration with inference terminals

However, the most exciting part of this release is the refined models that have been made judicious for applying dialogs using RLHF (Reinforcement Learning from Human Feedback). Across a wide range of help and security measures, Llama 2 chat models performed better than most open models, achieving comparable performance to ChatGPT based on human evaluations. Read on to learn about text generation inference and inference endpoints. Text Generation Inference is a production-ready inference wrapper developed by Hugging Face to enable easy implementation of large language models.

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It features continuous batching, token streaming, and tensor parallelism for fast inference across multiple GPUs and production-ready logging and tracing. However, you can test text generation inference on your own infrastructure or you can use Hugging Face inference endpoints. You can learn more about how to implement Llama 2 with Hugging face inference endpoints on our blog. The blog includes information on supported hyperparameters and how to stream your response using Python and Javascript.

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Source: vtt.edu.vn

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