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---
license: apache-2.0
tags:
- pruned
- python
- optimized
- wanda
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
pipeline_tag: text-generation
---
# EXAONE-3.5-2.4B-Instruct-python-safe
> 🎯 **PYTHON-optimized** | πŸ“¦ **Safe** pruning | ⚑ **1% weights pruned**
This model is a **conservatively pruned** version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0).
## Performance Comparison
| Category | Original | Pruned | Change |
|----------|----------|--------|--------|
| **Python** | 0.0% | 0.0% ⭐ | β†’ |
| Html | 0.0% | 0.0% | β†’ |
| Trivia | 11.1% | 11.1% | β†’ |
| Math | 0.0% | 0.0% | β†’ |
| Reasoning | 0.0% | 0.0% | β†’ |
| Medical | 0.0% | 0.0% | β†’ |
| Linux | 0.0% | 0.0% | β†’ |
| Writing | 0.0% | 0.0% | β†’ |
**Average**: 1.4% β†’ 1.4% (+0.0%)
![Comparison Graph](comparison_graph.png)
## Quick Start
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("CompactAI/EXAONE-3.5-2.4B-Instruct-python-safe")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/EXAONE-3.5-2.4B-Instruct-python-safe")
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
| Property | Value |
|----------|-------|
| Base Model | [Qwen/Qwen2.5-0.5B,TinyLlama/TinyLlama-1.1B-Chat-v1.0,Qwen/Qwen3-1.7B,HuggingFaceTB/SmolLM3-3B,Qwen/Qwen3-0.6B,Qwen/Qwen2.5-3B-Instruct,LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B,TinyLlama/TinyLlama-1.1B-Chat-v1.0,Qwen/Qwen3-1.7B,HuggingFaceTB/SmolLM3-3B,Qwen/Qwen3-0.6B,Qwen/Qwen2.5-3B-Instruct,LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct) |
| Specialization | Python |
| Prune Mode | Safe |
| Weight Reduction | 1% weights pruned |
## License
This model inherits the license from the base model.