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

SmolLM3-3B-reasoning-medium

🎯 REASONING-optimized | 📦 Medium pruning | ⚡ 20% weights pruned

This model is a moderately pruned version of HuggingFaceTB/SmolLM3-3B, specialized for REASONING tasks using activation-aware weight pruning (Wanda-style).

✨ Key Features

  • Specialization: Optimized for Reasoning 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% 40.0% ↓ 40.0%
Html 0.0% 0.0%
Trivia 100.0% 80.0% ↓ 20.0%
Math 100.0% 100.0%
Reasoning N/A N/A
Medical 100.0% 100.0%
Linux 100.0% 100.0%
Writing 93.3% 73.3% ↓ 20.0%

Average: 81.9% → 70.5% (-11.4%)

Comparison Graph

🚀 Quick Start

from transformers import AutoModelForCausalLM, AutoTokenizer

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


Generated by ZANNPS [Zeto Automatic Neural Network Pruning System]