https://github.com/gavinhome/mabysm-blog

This repository serves as knowledge base. The main focus is on the practical application of large models, including industry data fine-tuning, large model evaluation, and large model applications. All content is structured for easy navigation and learning.
https://github.com/gavinhome/mabysm-blog

adaptive-rag fine-tuning

Last synced: 8 months ago
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This repository serves as knowledge base. The main focus is on the practical application of large models, including industry data fine-tuning, large model evaluation, and large model applications. All content is structured for easy navigation and learning.

• Host: GitHub
• URL: https://github.com/gavinhome/mabysm-blog
• Owner: GavinHome
• License: agpl-3.0
• Created: 2025-09-23T01:05:37.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-09-23T02:02:44.000Z (9 months ago)
• Last Synced: 2025-09-23T04:06:48.701Z (9 months ago)
• Topics: adaptive-rag, fine-tuning
• Language: Jupyter Notebook
• Homepage:
• Size: 1.43 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# mabysm-blog

This repository serves as my personal blog and knowledge base, featuring technical writings and interactive content. The main focus is on the practical application of large models, including industry data fine-tuning, large model evaluation, and large model applications. All content is structured for easy navigation and learning.

## Content Directories

- [Fine-Tuning-Medical-COT](Fine-Tuning-Medical-COT/README.md) - Contains notebooks for fine-tuning medical Chain-of-Thought (COT) models using different language datasets (Chinese and English)

- [Grokking Algorithms](https://github.com/GavinHome/grokking_algorithms_code) - Contains code implementations for the book "Grokking Algorithms"

- [Langgraph-Adaptive-Rag](Langgraph-Adaptive-Rag/README.md) - Contains implementation of adaptive retrieval-augmented generation using Langgraph framework. See [README](Langgraph-Adaptive-Rag/README.md) for implementation details.