Finetuned Model For My Thesis: Design And Implementation Of An Adaptive Virtual Intelligent Teaching Assistant Based On Supervised Fine-tuning Of A Pre-trained Large Language Model

Model Name: CodeOptimus - Adaptive Supervised Instruction Fine-tuning Mistral 7B Instruct using qLora.

Prerequisites For Reproduction

  1. GPU: Requires powerful GPUs - I used 7 Nvidia A100s.
  2. Train Time: 1 week.
  3. RAG Module: Updates the knowledge base of the model in real-time with adaptive features learned from conversations with the model over time..
  4. Python Packages: Install requirements.txt.
  5. Dataset: Download code_instructions_122k_alpaca_style plus some custom curated dataset
  6. Mistra-7B-Instruct-v0.1: Download mistralai/Mistral-7B-Instruct-v0.1 pytorch bin weights
  7. Realistic 3D Intelligent Persona/Avatar (Optional): For this I'm using soulmachine's digital humans.

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Model size
7.24B params
Architecture
llama

5-bit

Inference API
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