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Announcing Llama 3.1 Support in vLLM
Today, the vLLM team is excited to partner with Meta to announce the support for the Llama 3.1 model series. Llama 3.1 comes with exciting new features with longer context length (up to 128K tokens), larger model size (up to 405B parameters), and more advanced model capabilities. The vLLM community has added many enhancements to make sure the longer, larger Llamas run smoothly on vLLM, which includes chunked prefill, FP8 quantization, and pipeline parallelism. We will introduce these new enhancements in this blogpost.
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Announcing Llama 3.1 Support in vLLM
Today, the vLLM team is excited to partner with Meta to announce the support for the Llama 3.1 model series. Llama 3.1 comes with exciting new features with longer context length (up to 128K tokens), larger model size (up to 405B parameters), and more advanced model capabilities. The vLLM community has added many enhancements to make sure the longer, larger Llamas run smoothly on vLLM, which includes chunked prefill, FP8 quantization, and pipeline parallelism. We will introduce these new enhancements in this blogpost.
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Announcing Llama 3.1 Support in vLLM
Today, the vLLM team is excited to partner with Meta to announce the support for the Llama 3.1 model series. Llama 3.1 comes with exciting new features with longer context length (up to 128K tokens), larger model size (up to 405B parameters), and more advanced model capabilities. The vLLM community has added many enhancements to make sure the longer, larger Llamas run smoothly on vLLM, which includes chunked prefill, FP8 quantization, and pipeline parallelism. We will introduce these new enhancements in this blogpost.
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