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---
title: CPU Only Zero Shot Text Classification
emoji: 🏃
colorFrom: gray
colorTo: purple
sdk: gradio
sdk_version: 5.31.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: ' CPU-only Zero-Shot Text Classification'
---
# 🏷️ Zero-Shot Text Classification
[](https://huggingface.co/spaces/your-username/zero-shot-classifier)
[]
[](https://huggingface.co/facebook/bart-large-mnli)
[](LICENSE)
---
## 🚀 Overview
Unlock **zero-shot classification** for any text—no fine-tuning required.
Define your own label set on the fly and see how well each label matches your input, powered by **BART-MNLI** on CPU.
> **AI buzzwords:**
> Natural Language Inference • Zero‐shot Learning • Transformer-based NLP • Real-time Inference • Edge Deployment • Cloud-native Demo
---
## ✨ Features
| 🔑 Feature | 🔍 Description |
|--------------------------------|----------------------------------------------------------------|
| **🚀 Zero-Shot** | Classify into arbitrary categories without task-specific data |
| **⚡ CPU-Only Inference** | Runs on free Hugging Face Spaces (2 vCPU / 16 GB RAM) |
| **🎛️ Single vs. Multi-Label** | Toggle between exclusive or overlapping labels |
| **🎨 Interactive UI** | Gradio Blocks with text input, label list, mode toggle, table |
| **🔧 No Training Needed** | Leverages pre-trained BART-MNLI via HF Transformers |
| **☁️ Instant Deploy** | Commit three files—Spaces auto-builds & hosts your demo |
---
## 🏗️ How It Works
1. **User Input** – Paste any sentence or paragraph.
2. **Label Definition** – Enter comma-separated candidate labels (e.g. “Positive, Negative, Question”).
3. **Model Inference** – Pipeline computes entailment scores for each label.
4. **Result Table** – Display each label with its confidence score.
All done **locally on the Space**, ensuring **privacy**, **zero API cost**, and **lightning speed**.
---
## 🛠️ Local Development
```bash
git clone https://github.com/your-username/zero-shot-classifier.git
cd zero-shot-classifier
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt
python app.py
## Latest Update
- Updated BART-MNLI model for better accuracy. - May 29, 2025 📝
- Enhanced Gradio UI responsiveness. - June 20, 2025 📝
- Improved multi-label classification support. - June 19, 2025 📝
- Updated BART-MNLI model for better accuracy. - June 18, 2025 📝
- Optimized CPU inference speed. 🧠 - June 17, 2025 📝
- Added support for custom label sets. ⚡ - June 16, 2025 📝
- Enhanced Gradio UI responsiveness. - June 15, 2025 📝
- Improved multi-label classification support. - June 14, 2025 📝
- Updated BART-MNLI model for better accuracy. 🧠 - June 13, 2025 📝
- Optimized CPU inference speed. - June 12, 2025 📝
- Added support for custom label sets. - June 11, 2025 📝
- Enhanced Gradio UI responsiveness. - June 10, 2025 📝
- Improved multi-label classification support. 🏷️ - June 09, 2025 📝
- Updated BART-MNLI model for better accuracy. - June 08, 2025 📝
- Optimized CPU inference speed. ⚡ - June 07, 2025 📝
- Added support for custom label sets. - June 06, 2025 📝
- Enhanced Gradio UI responsiveness. 🚀 - June 05, 2025 📝
- Improved multi-label classification support. 🎛️ - June 04, 2025 📝
- Updated BART-MNLI model for better accuracy. 🎛️ - June 03, 2025 📝
- Optimized CPU inference speed. ⚡ - June 02, 2025 📝
- Added support for custom label sets. 🧠 - June 01, 2025 📝
- Enhanced Gradio UI responsiveness. 🚀 - May 31, 2025 📝
- Improved multi-label classification support. 🏷️ - May 30, 2025 📝
**Website**: https://ghostainews.com/
**Discord**: https://discord.gg/BfA23aYz |