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README.md

@@ -5,7 +5,6 @@ tags:
 - python
 - optimized
 - wanda
-- activation-pruning
 base_model: LGAI-EXAONE/EXAONE-4.0-1.2B
 pipeline_tag: text-generation
 ---
@@ -14,35 +13,28 @@ pipeline_tag: text-generation
 
 > 🎯 **PYTHON-optimized** | 📦 **Safe** pruning | ⚡ **1% weights pruned**
 
-This model is a **conservatively pruned** version of [LGAI-EXAONE/EXAONE-4.0-1.2B](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-1.2B), specialized for **PYTHON** tasks using activation-aware weight pruning (Wanda-style).
+This model is a **conservatively pruned** version of [LGAI-EXAONE/EXAONE-4.0-1.2B](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-1.2B).
 
-## ✨ Key Features
-
-- **Specialization**: Optimized for Python tasks
-- **Pruning Method**: Wanda-style (|W| × |activation|) importance scoring
-- **Size Reduction**: 1% weights pruned
-- **Use Case**: High accuracy retention, ideal for production use
-
-## 📊 Performance Comparison
+## Performance Comparison
 
 | Category | Original | Pruned | Change |
 |----------|----------|--------|--------|
-| **Python** | 20.0% | 20.0% ⭐ | → |
-| Html | 6.7% | 0.0% | ↓ 6.7% |
-| Trivia | 26.7% | 33.3% | ↑ 6.7% |
-| Math | 60.0% | 60.0% | → |
-| Reasoning | 60.0% | 60.0% | → |
-| Medical | 73.3% | 73.3% | → |
-| Linux | 93.3% | 93.3% | → |
-| Writing | 60.0% | 60.0% | → |
+| **Python** | 76.9% | 76.9% ⭐ | → |
+| Html | 20.0% | 20.0% | → |
+| Trivia | 0.0% | 0.0% | → |
+| Math | 80.0% | 80.0% | → |
+| Reasoning | 0.0% | 0.0% | → |
+| Medical | 0.0% | 0.0% | → |
+| Linux | 0.0% | 0.0% | → |
+| Writing | 0.0% | 0.0% | → |
 
-**Average**: 50.0% → 50.0% (+0.0%)
+**Average**: 22.1% → 22.1% (+0.0%)
 
-**Python Retention**: 100.0% of original performance
+**Python Retention**: 100.0%
 
 ![Comparison Graph](comparison_graph.png)
 
-## 🚀 Quick Start
+## Quick Start
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
@@ -50,31 +42,20 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 model = AutoModelForCausalLM.from_pretrained("CompactAI/EXAONE-4.0-1.2B-python-safe")
 tokenizer = AutoTokenizer.from_pretrained("CompactAI/EXAONE-4.0-1.2B-python-safe")
 
-# 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
+## Technical Details
 
 | Property | Value |
 |----------|-------|
 | Base Model | [LGAI-EXAONE/EXAONE-4.0-1.2B](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-1.2B) |
 | Specialization | Python |
 | Prune Mode | Safe |
-| Pruning Method | Activation-based weight pruning (Wanda) |
 | Weight Reduction | 1% weights pruned |
 
-## 🔗 Related Models
-
-This model is part of the **EXAONE-4.0-1.2B** pruned model collection. Variants:
-- **Safe** - Conservative pruning (~10-20%), high accuracy retention
-- **Aggressive** - Maximum compression (~40-50%), best for edge deployment
+## License
 
-## 📜 License
-
-This model inherits the license from the base model [LGAI-EXAONE/EXAONE-4.0-1.2B](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-1.2B).
-
----
-*Generated by ZANNPS [Zeto Automatic Neural Network Pruning System]*
+This model inherits the license from the base model.

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1cd8feb5a5590a991f07bec7ae7f01ec2758d60707a84482c411390698410b3b
+oid sha256:ee58214bfb1aacb566e54820e60a427826b7669459ec20422c5124f94d9abb42
 size 2558820960

tokenizer.json

@@ -2,7 +2,7 @@
   "version": "1.0",
   "truncation": {
     "direction": "Right",
-    "max_length": 64512,
+    "max_length": 65386,
     "strategy": "LongestFirst",
     "stride": 0
   },