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# Mixtral-Experiment Series
# LLM-Experiment Series
Welcome to the Mixtral-Experiment series! This series of notebooks and scripts aims to provide a comprehensive guide on investigating the internal workings of Large Language Models (LLMs), understanding how they process inputs, and experimenting with their architectures.
Welcome to the LL-Experiment series! This series of notebooks and scripts aims to provide a comprehensive guide on investigating the internal workings of Large Language Models (LLMs), understanding how they process inputs, and experimenting with their architectures.
## Table of Contents
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## Series Overview
The Mixtral-Experiment series will cover the following topics:
The LLM-Experiment series will cover the following topics:
1. **Understanding LLM Architectures**:
- An overview of popular LLM architectures like Transformers, BERT, and Mixtral.
- Detailed explanations of key components such as embedding layers, self-attention mechanisms, and Mixture of Experts (MoE) layers.
- An overview of popular open source LLM architectures like Whisper, Llama, and Mixtral.
- Key trouble shooting during experimentation
2. **Investigating Input Processing**:
- How inputs are tokenized and embedded.