Metadata-Version: 2.1
Name: deploy-transformers
Version: 0.1
Summary: Easily deploy HuggingFace Transformers on a website
Home-page: https://github.com/aquadzn/deploy-transformers
Author: William Jacques
Author-email: williamjcqs8@gmail.com
License: UNKNOWN
Description: # 🚀 Deploy Transformers 🤗
        > Deploy a SOTA model for text-generation in just three lines of code 💻
        
        
        ![image](https://svgshare.com/i/GoN.svg)
        
        
        ## Installation
        
        [**Pytorch**](https://pytorch.org/get-started/locally/#start-locally) and [**Transformers**](https://github.com/huggingface/transformers/#installation) are obviously needed.
        
        ```bash
        pip install deploy-transformers
        ```
        
        **For deployment, file structure needs to be like this:**
        ```bash
        ├── static
        │   ├── script.js
        │   ├── style.css
        ├── templates
        │   ├── 404.html
        │   ├── index.html
        |
        └── your_file.py
        ```
        
        You can either **clone** this repository to have original files or use the function `website.create_structure()` or **create yourself** the structure.
        
        `website.create_structure()` will automatically create *templates/*, *static/* and all the files that are in it (.html, .js, .css).
        
        
        ## Usage
        
        Check the *[examples/](github.com/aquadzn/deploy-transformers/tree/master/examples)* folder.
        
        ```python
        # Deployment
        from deploy_transformers import Website
        
        website = Website(model_type="gpt2", model_name="distilgpt2")
        # website.create_folder(homepage_file="index.html", template_folder='templates', static_folder='static')
        website.deploy()
        ```
        
        **You can change homepage filename, templates/ and static/ names in `website.deploy()` but it's better to keep them as default.**
        
        ```python
        # Only text generation
        from deploy_transformers import ListModels, Model
        
        # ListModels() to show available models
        model = Model("gpt2", "distilgpt2", seed=42, verbose=False)
        model.generate(length=20, prompt="The quick brown fox jumps over the lazy dog")
        # If no prompt, input will be ask until exit
        ```
        
        ## Thanks
        
        * [Transformers](https://github.com/huggingface/transformers) package by HuggingFace
        * [gpt-2-cloudrun](https://github.com/minimaxir/gpt-2-cloud-run) by minimaxir
        
        ## Notes
        
        * Do the same but for other tasks like sentiment analysis, or Q&A.
        * Add Flask option?
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
