TinyLlama 1.1B LLM RAG Research Chatbot llamaindex Colab Demo Small LLM Amazing performance

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“The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs 🚀🚀. I try out TinyLlama 1.1B LLM as part of a RAG based research chatbot created using llamaindex. We adopted exactly the same architecture and tokenizer as Llama 2. This means TinyLlama can be plugged and played in many open-source projects built upon Llama. Besides, TinyLlama is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint.”
I try out the model as part of a RAG based research chatbot
Colab notebook: colab.research...
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[@flossoul]

Thank you for the tutorial, is normal that the VectorStoreIndex take so long for finish before start the gradio interface?

[@RitheshSreenivasan]

Depends on the document size

[@sriharsha5701]

Hi sir u r videos are so useful in my day today tasks is it possible to create an interactive chat bot for csv data set with all open source

[@RitheshSreenivasan]

Thank You. It should be possible

[@vidyuthkrishna]

ModuleNotFoundError: No module named 'llama_index.prompts'
I tried !pip install llama_index, it doesn't work..

[@RitheshSreenivasan]

try pip install llama_index==0.9.24