Update README.md

README.md

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----
-title: Salesforce Codet5 Large
-emoji: ⚡
-colorFrom: indigo
-colorTo: gray
-sdk: gradio
-sdk_version: 5.23.3
-app_file: app.py
-pinned: false
-license: apache-2.0
-hf_oauth: true
-hf_oauth_scopes:
-- inference-api
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Salesforce CodeT5 Large Demo
+emoji: ⚡
+colorFrom: indigo
+colorTo: gray
+sdk: gradio
+sdk_version: 5.23.3
+app_file: app.py
+pinned: false
+license: apache-2.0
+datasets:
+- CodeSearchNet/codesearchnet_python
+- bigcode/the-stack-dedup
+- codeparrot/codeparrot-clean
+- openai_humaneval
+- google/mbpp
+hf_oauth: true
+hf_oauth_scopes:
+- inference-api
+short_description: Using the powerful Salesforce CodeT5-large model
+---
+
+# ⚡ Salesforce CodeT5-large Demo ⚡
+
+Welcome! This repository/Hugging Face Space hosts a demonstration application for the powerful [Salesforce CodeT5-large](https://huggingface.co/Salesforce/codet5-large) model. It showcases the model's capabilities in various code intelligence tasks using a Gradio interface.
+
+## About CodeT5-large
+
+CodeT5 is an advanced encoder-decoder transformer model pre-trained on a vast collection of source code from multiple programming languages alongside natural language text. The `codet5-large` variant excels at tasks such as:
+
+* **Code Generation:** Creating code snippets from natural language descriptions (e.g., comments, docstrings).
+* **Code Summarization:** Generating concise natural language summaries for given code blocks.
+* **Code Translation:** Translating code from one programming language to another.
+* **Code Refinement:** Improving code quality, fixing bugs, or optimizing code.
+
+## Using the Demo (Hugging Face Space)
+
+This application is built with Gradio, providing an interactive web UI.
+
+1.  **Access the Space:** Navigate to the Hugging Face Space hosting this demo.
+2.  **Interact:** Use the input fields provided by the Gradio interface (`app.py`) to interact with the model.
+    * *(Example: You might enter a Python docstring in one box to get the generated function body in another, or input code to get a summary. Please update this section with specific instructions based on your `app.py` functionality!)*
+3.  **Observe:** See the results generated by the CodeT5-large model in the output fields.
+
+## Running Locally (GitHub / Manual Setup)
+
+If you prefer to run this demo on your local machine:
+
+1.  **Clone the Repository:**
+    ```bash
+    git clone <repository_url> # Replace with HF Space or GitHub repo URL
+    cd <repository_directory>
+    ```
+
+2.  **Set up Environment:** (Optional but recommended) Create and activate a virtual environment:
+    ```bash
+    python -m venv venv
+    source venv/bin/activate # Linux/macOS
+    # venv\Scripts\activate # Windows
+    ```
+
+3.  **Install Dependencies:** Ensure you have Python 3 installed. You'll need Gradio and the necessary libraries for CodeT5 (like `transformers` and `torch`). Create a `requirements.txt` file if one doesn't exist:
+    ```plaintext
+    # requirements.txt
+    gradio==5.23.3
+    transformers
+    torch
+    # Add any other specific libraries your app.py needs
+    ```
+    Then install:
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+4.  **Run the Application:**
+    ```bash
+    python app.py
+    ```
+
+5.  **Access Locally:** Open your web browser and navigate to the URL provided (typically `http://127.0.0.1:7860`).
+
+## Fine-tuning Datasets for Python & Logic
+
+The CodeT5 model's performance on specific Python tasks or logical reasoning can be enhanced through fine-tuning. Here are some recommended datasets included in the metadata:
+
+* [**CodeSearchNet (Python)**](https://huggingface.co/datasets/CodeSearchNet): Excellent for tasks involving matching natural language queries to relevant Python code snippets.
+* [**The Stack (Deduped)**](https://huggingface.co/datasets/bigcode/the-stack-dedup): A massive, permissively licensed dataset. Filter for Python files (`lang:python`) for broad fine-tuning on diverse Python code.
+* [**CodeParrot (Clean)**](https://huggingface.co/datasets/codeparrot/codeparrot-clean): A high-quality dataset specifically curated for Python code generation tasks.
+* [**HumanEval**](https://huggingface.co/datasets/openai_humaneval): A benchmark dataset consisting of Python function programming problems defined by docstrings, ideal for fine-tuning code generation based on specifications and evaluating functional correctness.
+* [**MBPP (Mostly Basic Python Problems)**](https://huggingface.co/datasets/google/mbpp): Contains around 1,000 crowd-sourced Python programming problems focused on basic concepts, useful for improving generation from descriptions and simple logical problem-solving.
+
+## License
+
+This project and the underlying CodeT5 model are distributed under the terms of the [Apache License 2.0](LICENSE). Please refer to the LICENSE file for details.