EXAONE-4.0-1.2B
Collection
Collection of pruned models based on EXAONE-4.0-1.2B
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16 items
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Updated
🎯 PYTHON-optimized | 📦 Aggressive pruning | ⚡ 30% weights pruned
This model is a aggressively pruned version of LGAI-EXAONE/EXAONE-4.0-1.2B.
| Category | Original | Pruned | Change |
|---|---|---|---|
| Python | 76.9% | 61.5% ⭐ | ↓ 15.4% |
| Html | 20.0% | 10.0% | ↓ 10.0% |
| Trivia | 86.7% | 53.3% | ↓ 33.3% |
| Math | 80.0% | 93.3% | ↑ 13.3% |
| Reasoning | 75.0% | 50.0% | ↓ 25.0% |
| Medical | 42.9% | 14.3% | ↓ 28.6% |
| Linux | 23.1% | 23.1% | → |
| Writing | 54.5% | 0.0% | ↓ 54.5% |
Average: 57.4% → 38.2% (-19.2%)
Python Retention: 80.0%
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("CompactAI/EXAONE-4.0-1.2B-python-aggressive")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/EXAONE-4.0-1.2B-python-aggressive")
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 | Aggressive |
| Weight Reduction | 30% weights pruned |
This model inherits the license from the base model.
Base model
LGAI-EXAONE/EXAONE-4.0-1.2B