https://github.com/kevinknights29/databricks_llm101x

This project contains the lab notebooks from course: Large Language Models: Application through Production by Databricks
https://github.com/kevinknights29/databricks_llm101x

databricks jupyter-notebook llms

Last synced: 23 days ago
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This project contains the lab notebooks from course: Large Language Models: Application through Production by Databricks

• Host: GitHub
• URL: https://github.com/kevinknights29/databricks_llm101x
• Owner: kevinknights29
• License: other
• Created: 2023-09-21T03:32:58.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-04-24T02:47:03.000Z (7 months ago)
• Last Synced: 2024-05-08T00:23:58.127Z (6 months ago)
• Topics: databricks, jupyter-notebook, llms
• Language: Jupyter Notebook
• Homepage:
• Size: 11 MB
• Stars: 2
• Watchers: 1
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Databricks_LLM101x

This project contains the lab notebooks from course: Large Language Models: Application through Production by Databricks

## Modules

1. LLMs with Hugging Face

2. Embeddings, Vector DBs, and Search

3. Building LLM Chains

4. LLM Evaluation

## Usage

To run Databricks' labs you can leverage Docker with the instructions below:

1. For first time usage, you need to build the Docker image:

    ```bash

    docker compose build .

    ```

2. After that you can start the container with:

    ```bash

    docker compose up -d

    ```

3. Go to Docker desktop, to retrieve your jupyterlab access URL.

    - Click the container name, to open the logs.

    - Retrive the jupyterlab URL, it should look like: `http://127.0.0.1:8888/lab?token=4150032f3603c85febf54b8b40bb761a2eb46e2fb593d5dc`

    ![image](https://github.com/kevinknights29/Airflow_Docs_LLM_App/assets/74464814/661f3747-2b2e-4387-9c79-64af1d8bc56e)

4. To stop the container, run:

    ```bash

    docker compose down

    ```