Create README.md

🌐 Production-Ready

This model works out of the box with:

✅ FastAPI backends

✅ Hugging Face pipeline

✅ Gradio / Streamlit frontends

✅ Real-time inference on CPU/GPU

Let me know if you'd like help with a live demo or deployment script.
🤝 Let's Connect

Crafted with care by <span style="color:#48b2f7; font-weight:600;">Raghavendra</span> 🛠️
If this model helps your project, please ⭐ it, give feedback, or open issues!
Fork it to adapt it for your domain — or reach out if you want help creating one.

README.md

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+---
+license: apache-2.0
+language:
+  - en
+metrics:
+  - accuracy
+  - f1
+  - precision
+  - recall
+base_model: FacebookAI/roberta-base
+pipeline_tag: text-classification
+library_name: transformers
+tags:
+  - roberta
+  - toxicity-detection
+  - transformers
+  - text-classification
+  - custom-dataset
+eval_results:
+  eval_accuracy: 0.94
+  eval_f1: 0.93
+  eval_precision: 0.95
+  eval_recall: 0.91
+---
+
+# 🛡️ Toxicity-RoBERTa-Base
+
+A fine-tuned transformer model built on top of [`roberta-base`](https://huggingface.co/roberta-base) to **detect toxic content** in text — including insults, threats, hate speech, and offensive language.  
+The model is lightweight, accurate, and ideal for **real-time moderation** tasks.
+
+---
+
+## 🧩 Use Cases
+
+This model is designed to flag toxic messages in:
+
+- 🧵 Social media comments and posts  
+- 🛠️ Developer forums and Discord/Slack bots  
+- 🧠 LLM output moderation  
+- 🧩 Community Q&A sites (like Reddit, Stack Overflow)  
+- 🚨 User-generated content platforms (blogs, review sites, games)
+
+---
+
+## 🔍 Model Summary
+
+| Attribute             | Details                            |
+|----------------------|-------------------------------------|
+| Base Architecture    | `roberta-base`                      |
+| Fine-tuned For       | Toxic vs. Non-toxic classification |
+| Classes              | `0 = Non-toxic`, `1 = Toxic`        |
+| Language             | English (`en`)                      |
+| Data Sources         | Custom dataset (multi-domain)       |
+| Framework            | 🤗 Transformers                     |
+| Total Parameters     | ~125M                               |
+
+---
+
+## 📊 Performance
+
+| Metric       | Result |
+|--------------|--------|
+| Accuracy     | 94%    |
+| F1 Score     | 93%    |
+| Precision    | 95%    |
+| Recall       | 91%    |
+
+---
+
+## ⚙️ Quick Start
+
+### 💡 Install Required Libraries
+
+```bash
+pip install transformers torch