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---
license: apache-2.0
tags:
- pruned
- math
- optimized
- wanda
base_model: tiiuae/Falcon-H1-Tiny-R-0.6B
pipeline_tag: text-generation
---
# Falcon-H1-Tiny-R-0.6B-math-aggressive
> 🎯 **MATH-optimized** | πŸ“¦ **Aggressive** pruning | ⚑ **1% weights pruned**
This model is a **aggressively pruned** version of [tiiuae/Falcon-H1-Tiny-R-0.6B](https://huggingface.co/tiiuae/Falcon-H1-Tiny-R-0.6B).
## Performance Comparison
| Category | Original | Pruned | Change |
|----------|----------|--------|--------|
| Python | 0.0% | 0.0% | β†’ |
| Html | 0.0% | 0.0% | β†’ |
| Trivia | 0.0% | 0.0% | 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**: 0.0% β†’ 0.0% (+0.0%)
![Comparison Graph](comparison_graph.png)
## Quick Start
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("CompactAI/Falcon-H1-Tiny-R-0.6B-math-aggressive")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/Falcon-H1-Tiny-R-0.6B-math-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))
```
## Technical Details
| Property | Value |
|----------|-------|
| Base Model | [tiiuae/Falcon-H1-Tiny-R-0.6B](https://huggingface.co/tiiuae/Falcon-H1-Tiny-R-0.6B) |
| Specialization | Math |
| Prune Mode | Aggressive |
| Weight Reduction | 1% weights pruned |
## License
This model inherits the license from the base model.