SmolLM3-3B
Collection
Collection of pruned models based on HuggingFaceTB/SmolLM3-3B
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56 items
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Updated
🎯 HTML-optimized | 📦 Medium pruning | ⚡ 20% weights pruned
This model is a moderately pruned version of HuggingFaceTB/SmolLM3-3B, specialized for HTML tasks using activation-aware weight pruning (Wanda-style).
| 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%)
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))
| Property | Value |
|---|---|
| Base Model | HuggingFaceTB/SmolLM3-3B |
| Specialization | Html |
| Prune Mode | Medium |
| Pruning Method | Activation-based weight pruning (Wanda) |
| Weight Reduction | 20% weights pruned |
This model is part of the SmolLM3-3B pruned model collection. Other variants:
This model inherits the license from the base model HuggingFaceTB/SmolLM3-3B.
Generated by ZANNPS [Zeto Automatic Neural Network Pruning System]
Base model
HuggingFaceTB/SmolLM3-3B-Base