Building an LLM fine-tuning Dataset

Building an LLM Fine-tuning Dataset Step-by-Step Tutorial:

1. Introduction to Reddit Data Set Creation:

   • The video discusses creating a Reddit data set for LLM fine-tuning.
   • Focus on data set curation and the process involved in creating around 35,000 samples.
   • Mention of ways to filter and curate data sets for specific subreddits.

2. Initial Data Gathering:

   • Start by finding a Reddit thread with available comments.
   • Consider using tools like BigQuery to access Reddit data from 2005 to 2019.
   • Download the desired Reddit data sets for further processing.

3. Data Formatting:

   • Decompress the downloaded files if needed before processing.
   • Use Python scripts to extract, clean, and format the data for training.

4. Data Set Creation:

   • Load the formatted data into a DataFrame for further manipulation.
   • Filter the data based on criteria like minimum score and length to refine the data set.

5. Preparing for Fine-Tuning:

   • Upload the curated data set to platforms like Hugging Face for easy access and sharing.
   • Choose a suitable model for fine-tuning, such as Llama 27B, and set up the training environment.

6. Model Fine-Tuning:

   • Utilize AutoPFT models for causal LM to fine-tune the chosen model efficiently.
   • Experiment with different training steps, adapters, and model configurations to optimize performance.

7. Testing and Evaluation:

   • Test the fine-tuned model with sample prompts to evaluate its conversational capabilities.
   • Consider filtering out low-quality samples and refining the data set further for improved results.

8. Deployment and Sharing:

   • Share the fine-tuned model and data set for others to use and experiment with.
   • Provide links and resources for accessing the model, data set, and related tools.

9. Bonus: GPU Giveaway and Additional Resources:

   • Mention the GPU giveaway for signing up for GTC and attending sessions.
   • Encourage feedback, suggestions, and ideas for future data set creation and model fine-tuning projects.

10. Conclusion:

    • Summarize the process of creating an LLM fine-tuning data set from Reddit data.
    • Highlight the importance of data curation, model selection, and continuous experimentation for optimal results.

By following these steps, you can create and fine-tune a Language Model using Reddit data sets efficiently.