EXAONE-4.0-1.2B
Collection
Collection of pruned models based on LGAI-EXAONE/EXAONE-4.0-1.2B
•
56 items
•
Updated
🎯 PYTHON-optimized | 📦 Extra Heavy pruning | ⚡ 25% weights pruned
This model is a extremely pruned version of LGAI-EXAONE/EXAONE-4.0-1.2B, specialized for PYTHON tasks using activation-aware weight pruning (Wanda-style).
| Category | Original | Pruned | Change |
|---|---|---|---|
| Python | 20.0% | 20.0% ⭐ | → |
| Html | 6.7% | 0.0% | ↓ 6.7% |
| Trivia | 86.7% | 66.7% | ↓ 20.0% |
| Math | 60.0% | 40.0% | ↓ 20.0% |
| Reasoning | N/A | N/A | |
| Medical | 93.3% | 66.7% | ↓ 26.7% |
| Linux | 93.3% | 86.7% | ↓ 6.7% |
| Writing | 46.7% | 26.7% | ↓ 20.0% |
Average: 58.1% → 43.8% (-14.3%)
Python Retention: 100.0% of original performance
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("CompactAI/EXAONE-4.0-1.2B-python-extra-heavy")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/EXAONE-4.0-1.2B-python-extra-heavy")
# 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 | Python |
| Prune Mode | Extra Heavy |
| Pruning Method | Activation-based weight pruning (Wanda) |
| Weight Reduction | 25% 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