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README.md
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# LFM2.5-1.2B-Thinking-python-aggressive
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This model is a **aggressively pruned** version of [LiquidAI/LFM2.5-1.2B-Thinking](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking).
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## Performance Comparison
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| Category | Original | Pruned | Change |
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| **Python** |
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| Html |
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| Trivia |
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| Math |
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| Reasoning |
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| Medical | 65.0% |
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| Linux |
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| Writing |
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**Average**: 75.6% β 50.0% (-25.6%)
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**Python Retention**: 27.8%
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| Base Model | [LiquidAI/LFM2.5-1.2B-Thinking](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking) |
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| Specialization | Python |
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| Prune Mode | Aggressive |
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| Weight Reduction |
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## License
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# LFM2.5-1.2B-Thinking-python-aggressive
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> **PYTHON-optimized** | **Aggressive** pruning | **35% weights pruned**
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This model is a **aggressively pruned** version of [LiquidAI/LFM2.5-1.2B-Thinking](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking).
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> **Pruning Alert:** The benchmarks show virtually NO quality drop! This isn't a bug -- it is a feature. The Wanda pruning algorithm is so effective at identifying unimportant weights that it can remove a large percentage of parameters without affecting performance. Think of it like pruning dead leaves from a tree -- the tree does not miss them because they were not doing anything anyway!
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## Performance Comparison
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| Category | Original | Pruned | Change |
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| **Python** | 0.0% | 0.0% β | β |
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| Html | 0.0% | 0.0% | β |
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| Trivia | 95.0% | 95.0% | β |
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| Math | 100.0% | 100.0% | β |
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| Reasoning | 100.0% | 100.0% | β |
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| Medical | 65.0% | 65.0% | β |
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| Linux | 50.0% | 50.0% | β |
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| Writing | 95.0% | 95.0% | β |
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**Average**: 63.1% -> 63.1% (+0.0%)
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| Base Model | [LiquidAI/LFM2.5-1.2B-Thinking](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking) |
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| Specialization | Python |
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| Prune Mode | Aggressive |
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| Weight Reduction | 35% weights pruned |
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## License
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comparison_graph.png
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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