I'm trying to integrate an open-source 20 billion parameter model with LlamaIndex for my project. However, I'm facing challenges in setting it up properly. What are the necessary steps to run a 20B model within the LlamaIndex framework? Are there specific configurations or optimizations I should consider for handling such a large model? What are the common pitfalls or issues I should be aware of when working with LlamaIndex and large models? I have attempted to load the 20B model using the standard LlamaIndex setup, following the documentation provided. I configured the model parameters and ensured that my environment has sufficient resources (like GPU memory) to handle the model's requirements. I expected the model to initialize successfully and be able to process queries efficiently. However, I encountered issues with memory allocation and performance lag during inference. I was hoping to achieve smooth integration and fast response times, similar to what I’ve seen in examples with smaller models. Continue reading...
