Update README.md

README.md

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+Exllama 4 bit version, original model card below. 
 
 ## Model Details
 We introduce Llama3-ChatQA-2, a suite of 128K long-context models, which bridges the gap between open-source LLMs and leading proprietary models (e.g., GPT-4-Turbo) in long-context understanding and retrieval-augmented generation (RAG) capabilities. Llama3-ChatQA-2 is developed using an improved training recipe from [ChatQA-1.5 paper](https://arxiv.org/pdf/2401.10225), and it is built on top of [Llama-3 base model](https://huggingface.co/meta-llama/Meta-Llama-3-70B). Specifically, we continued training of Llama-3 base models to extend the context window from 8K to 128K tokens, along with a three-stage instruction tuning process to enhance the model’s instruction-following, RAG performance, and long-context understanding capabilities. Llama3-ChatQA-2 has two variants: Llama3-ChatQA-2-8B and Llama3-ChatQA-2-70B. Both models were originally trained using [Megatron-LM](https://github.com/NVIDIA/Megatron-LM), we converted the checkpoints to Hugging Face format. **For more information about ChatQA 2, check the [website](https://chatqa2-project.github.io/)!**