---
title: BERT CryptoTalk
emoji: 📈
colorFrom: gray
colorTo: yellow
sdk: gradio
sdk_version: 6.14.0
app_file: app.py
pinned: false
license: mit
short_description: BERT-CryptoTalk
hf_oauth: true
hf_oauth_scopes:
- inference-api
---

# 🪙 CryptoBERT Gradio Inference App

A clean, modern Gradio interface for **CryptoBERT**, a fine-tuned BERT model for cryptocurrency-related text classification — complete with Hugging Face authentication management, dynamic token updates, and integrated sample dataset previews.

---

## 📦 Features

✅ **CryptoBERT Text Classification**  
✅ **Gradio UI with Sidebar & Tabs**  
✅ **Dynamic Hugging Face Token Authentication**  
✅ **Secure Token Management with .env Support**  
✅ **Sample Dataset Preview (AG News)**  
✅ **Structured, Testable Python Codebase**  
✅ **PEP 8 & Security Best Practices**  
✅ **Unit Testing Included**  

---

## 📸 Demo Preview

![demo-preview](https://user-images.githubusercontent.com/your-demo-image.png)

---

## 🚀 Quickstart

### 1️⃣ Clone the Repository  
```bash
git clone https://github.com/your-username/crypto-bert-inference.git
cd crypto-bert-inference
```

### 2️⃣ Install Dependencies  
```bash
pip install -r requirements.txt
```

### 3️⃣ Configure Environment Variables  

Create a `.env` file:
```bash
cp .env.example .env
```

Edit `.env`:
```dotenv
HUGGINGFACE_TOKEN=your_huggingface_token_here
```

### 4️⃣ Launch the App  
```bash
python app.py
```

The Gradio interface will open in your browser.

---

## 📊 Usage

### 🔐 Authenticate with Hugging Face  
- Enter your Hugging Face token in the sidebar
- Click `Set Token` to authenticate dynamically

### 📝 Run Crypto Sentiment Inference  
- Switch to the `CryptoTalk Inference` tab  
- Enter cryptocurrency-related text  
- Click `Predict` to view sentiment predictions  

### 📖 View Sample Dataset  
- The sidebar displays a preview sample from the `AG News` dataset for demo purposes  

---

## 🗂️ Project Structure  

```
crypto-bert-inference/
├── app.py
├── pipeline_utils.py
├── .env
├── requirements.txt
├── tests/
│   └── test_app.py
└── README.md
```

---

## 🧪 Run Unit Tests  

```bash
python -m unittest discover tests
```

---

## 📚 Dependencies  

- [transformers](https://github.com/huggingface/transformers)  
- [gradio](https://gradio.app)  
- [datasets](https://huggingface.co/docs/datasets)  
- [python-dotenv](https://github.com/theskumar/python-dotenv)  
- [requests](https://docs.python-requests.org/en/latest/)  

---

## 📖 Documentation  

- [CryptoBERT Model (kk08/CryptoBERT)](https://huggingface.co/kk08/CryptoBERT)
- [Gradio Blocks API](https://www.gradio.app/docs/blocks)
- [Hugging Face Authentication API](https://huggingface.co/docs/hub/security-tokens)

---

## 💡 Future Enhancements  

- 🐳 Dockerized deployment  
- 📈 Inference result charting  
- 🌐 Web-hosted demo on Hugging Face Spaces  

---

## 🛡️ Security Considerations  

- Tokens are stored securely via environment variables
- No plaintext token persistence or hardcoding
- Input validation handled by Transformers pipelines
- Isolated inference processes

---

## 📜 License  

MIT © [Canstralian(https://github.com/canstralian)

---

## 🖥️ Author  

**[Your Name]** — *Cybersecurity & AI Developer*  
[GitHub](https://github.com/canstralian) | [LinkedIn](https://www.linkedin.com/in/stephen-de-jager-71b52b29b/)

```