EXAONE-4.0-1.2B
Collection
Collection of pruned models based on LGAI-EXAONE/EXAONE-4.0-1.2B
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56 items
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Updated
🎯 HTML-optimized | 📦 Medium Light pruning | ⚡ 30% weights pruned
This model is a moderate-lightly pruned version of LGAI-EXAONE/EXAONE-4.0-1.2B, specialized for HTML tasks using activation-aware weight pruning (Wanda-style).
| Category | Original | Pruned | Change |
|---|---|---|---|
| Python | 20.0% | 0.0% | ↓ 20.0% |
| Html | 6.7% | 0.0% ⭐ | ↓ 6.7% |
| Trivia | 86.7% | 60.0% | ↓ 26.7% |
| Math | 60.0% | 33.3% | ↓ 26.7% |
| Reasoning | N/A | N/A | |
| Medical | 93.3% | 60.0% | ↓ 33.3% |
| Linux | 93.3% | 86.7% | ↓ 6.7% |
| Writing | 46.7% | 13.3% | ↓ 33.3% |
Average: 58.1% → 36.2% (-21.9%)
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("CompactAI/EXAONE-4.0-1.2B-html-medium-light")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/EXAONE-4.0-1.2B-html-medium-light")
# 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 | LGAI-EXAONE/EXAONE-4.0-1.2B |
| Specialization | Html |
| Prune Mode | Medium Light |
| Pruning Method | Activation-based weight pruning (Wanda) |
| Weight Reduction | 30% weights pruned |
This model is part of the EXAONE-4.0-1.2B pruned model collection. Other variants:
This model inherits the license from the base model LGAI-EXAONE/EXAONE-4.0-1.2B.
Generated by ZANNPS [Zeto Automatic Neural Network Pruning System]
Base model
LGAI-EXAONE/EXAONE-4.0-1.2B