"~"

README.md

@@ -10,65 +10,50 @@ pinned: false
 license: apache-2.0
 ---
 
-# Text Summarization with Hugging Face Transformers and Gradio
+# Text Summarization Hugging Face Spaces App
 
-This project demonstrates text summarization using Hugging Face Transformers and Gradio. It provides an easy-to-use interface for summarizing text.
+Welcome to the Text Summarization Hugging Face Spaces App! This app allows you to generate text titles using the XJLULU/NTU_ADL_SUMMARIZATION_MT5_S model.
 
-## Demo
+## App Description
 
-You can try out the Text Summarization application [here](https://huggingface.co/spaces/xjlulu/summarization). Simply enter a piece of text, and the application will generate a summary for you.
+This app takes a piece of text as input and generates a summary of the text. You can either enter your own text or click the "Random" button to get a random example from a provided dataset and generate a summary.
 
-## Getting Started
+## How to Use
 
-### Prerequisites
+1. Enter or paste a piece of text into the "Context paragraph" textbox.
+2. Click the "Generate" button to generate a summary.
+3. You can also click the "Random" button to generate a random example for summarization.
 
-Before running the application, make sure you have Python and the required packages installed:
+## Example Data
 
-- Python 3.6+
-- Hugging Face Transformers
-- Gradio
+The app uses a dataset of examples provided in the `sample_data.jsonl` file. Each example in the dataset contains a "text" field. You can either provide your own text or use the "Random" button to choose an example from the dataset.
 
-You can install the necessary Python packages using `pip`:
+## Model Information
 
-```shell
-pip install transformers gradio
-```
+This project uses the `xjlulu/ntu_adl_summarization_mt5_s` model from Hugging Face.
 
-### Installation
 
-1. Clone this repository:
-```shell
-# Make sure you have git-lfs installed (https://git-lfs.com)
-git lfs install
-git clone https://huggingface.co/spaces/xjlulu/summarization
+## Local Setup
 
-# if you want to clone without large files – just their pointers
-# prepend your git clone with the following env var:
-GIT_LFS_SKIP_SMUDGE=1
-```
+If you want to run this app locally, follow these steps:
 
-2. Change to the project directory:
-```shell
-cd summarization
-```
-3. Run the application:
-```shell
-python app.py
-```
+1. Clone the repository: `git clone https://huggingface.co/spaces/xjlulu/summarization`
+2. Navigate to the project directory: `cd summarization`
+3. Install the required libraries: `pip install -r requirements.txt`
+4. Run the app: `python app.py`
 
-Your Gradio application should now be running, and you can access it at [http://localhost:7860](http://localhost:7860).
+The app will start locally and be accessible at `http://localhost:7860`. You can access it in your web browser.
 
-### Usage
+## Credits
 
-1. Enter a piece of text in the provided input field.
-2. Click the "Summarize" button.
-3. The application will generate a summary of the input text and display it.
+- [Hugging Face Transformers](https://github.com/huggingface/transformers)
+- [Gradio](https://gradio.app/)
+- [apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)
 
-### Contributing
+## License
 
-We welcome contributions from the community. If you find any issues or have ideas for improvements, please open an issue or submit a pull request.
+This project is licensed under the apache-2.0 - see the [apache-2.0](https://www.apache.org/licenses/LICENSE-2.0) file for details.
 
-### License
-
-This project is licensed under the [Apache License 2.0](LICENSE). See the [LICENSE](LICENSE) file for details.
+## Acknowledgments
 
+Thank you to the open-source community for developing the amazing tools and libraries that make this project possible.

app.py

@@ -26,7 +26,7 @@ with gr.Blocks(theme=gr.themes.Soft(), title="Text Summarization") as demo:
         gr.Markdown(description)
 
         C_input = gr.Textbox(lines=12, label="Context paragraph")
-        S_output = Textbox(lines=3, label="summary")
+        S_output = Textbox(lines=3, label="title")
         with gr.Row():
                 random_button = gr.Button("Random")
                 generate_button = gr.Button("Generate")

requirements.txt

@@ -1,5 +1,6 @@
 text-generation==0.6.0
 transformers==4.31.0
+gradio
 pymongo==4.4.1
 torch
 sentencepiece