https://github.com/esmail-ibraheem/tal

I developed a Python library for transformers, leveraging the architecture I previously designed. With this library, users can freely install and utilize the transformer architecture.
https://github.com/esmail-ibraheem/tal

library machine-learning pytorch transformer

Last synced: about 1 year ago
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I developed a Python library for transformers, leveraging the architecture I previously designed. With this library, users can freely install and utilize the transformer architecture.

• Host: GitHub
• URL: https://github.com/esmail-ibraheem/tal
• Owner: Esmail-ibraheem
• License: mit
• Created: 2024-02-28T12:26:27.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-04-16T07:09:13.000Z (about 2 years ago)
• Last Synced: 2025-04-08T21:41:58.907Z (about 1 year ago)
• Topics: library, machine-learning, pytorch, transformer
• Language: Python
• Homepage:
• Size: 141 KB
• Stars: 3
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Transformer Architecture Library

![image](https://github.com/Esmail-ibraheem/transformer-architecture-library/assets/113830751/8552eab6-0b7b-496b-848e-12b0476a7820)

I developed a Python library for transformers, leveraging the architecture I previously designed. With this library, users can freely install and utilize the transformer architecture.

---

1. Create a Directory Structure: Start by creating a directory structure for your package, For instance:

   - create a folder called transformer_package, then save this files in the folder.

    ```bash

    my_transformer_package/

    ├── my_transformer/

    │   ├── __init__.py

    │   ├── transformer.py

    └── setup.py

    ```

2. the setup.py: This file is used to define metadata about your package and how to install it. Here's a minimal example, you can change it for example the version:

   ```python

   from setuptools import setup, find_packages

   setup(

       name='transformer_lib',

       version='0.1',

       packages=find_packages(),

       install_requires=[

           'torch>=1.6.0',

       ],

       python_requires='>=3.6',

   )

   ```

3. After installing the repo, go to the terminal and type:

   ```bash

   pip install .

   ```

3. And then, run the test file.

   ### Now you should be able to use the transformer architecture in any python file you build.