---
license: apache-2.0
tags:
- pruned
- html
- optimized
- wanda
- activation-pruning
base_model: HuggingFaceTB/SmolLM3-3B
pipeline_tag: text-generation
---

# SmolLM3-3B-html-medium

> 🎯 **HTML-optimized** | 📦 **Medium** pruning | ⚡ **20% weights pruned**

This model is a **moderately pruned** version of [HuggingFaceTB/SmolLM3-3B](https://huggingface.co/HuggingFaceTB/SmolLM3-3B), specialized for **HTML** tasks using activation-aware weight pruning (Wanda-style).

## ✨ Key Features

- **Specialization**: Optimized for Html tasks
- **Pruning Method**: Wanda-style (|W| × |activation|) importance scoring
- **Size Reduction**: 20% weights pruned
- **Use Case**: Balanced trade-off between size and accuracy

## 📊 Performance Comparison

| Category | Original | Pruned | Change |
|----------|----------|--------|--------|
| Python | 80.0% | 60.0% | ↓ 20.0% |
| **Html** | 0.0% | 0.0% ⭐ | → |
| Trivia | 100.0% | 66.7% | ↓ 33.3% |
| Math | 100.0% | 100.0% | → |
| Reasoning | N/A | N/A |  |
| Medical | 100.0% | 93.3% | ↓ 6.7% |
| Linux | 100.0% | 80.0% | ↓ 20.0% |
| Writing | 93.3% | 86.7% | ↓ 6.7% |

**Average**: 81.9% → 69.5% (-12.4%)



![Comparison Graph](comparison_graph.png)

## 🚀 Quick Start

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("CompactAI/SmolLM3-3B-html-medium")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/SmolLM3-3B-html-medium")

# Example usage
inputs = tokenizer("Your prompt here", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## 📋 Technical Details

| Property | Value |
|----------|-------|
| Base Model | [HuggingFaceTB/SmolLM3-3B](https://huggingface.co/HuggingFaceTB/SmolLM3-3B) |
| Specialization | Html |
| Prune Mode | Medium |
| Pruning Method | Activation-based weight pruning (Wanda) |
| Weight Reduction | 20% weights pruned |

## 🔗 Related Models

This model is part of the **SmolLM3-3B** pruned model collection. Other variants:
- Extra-light (minimal pruning)
- Light
- Medium-light  
- Medium
- Medium-heavy
- Heavy
- Extra-heavy (maximum compression)

## 📜 License

This model inherits the license from the base model [HuggingFaceTB/SmolLM3-3B](https://huggingface.co/HuggingFaceTB/SmolLM3-3B).

---
*Generated by ZANNPS [Zeto Automatic Neural Network Pruning System]*