LFM2.5-1.2B-Instruct-python-safe

PYTHON-optimized | Safe pruning | 30% weights pruned

This model is a conservatively pruned version of LiquidAI/LFM2.5-1.2B-Instruct.

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!

Performance Comparison

Category	Original	Pruned	Change
Python	0.0%	0.0% ⭐	→
Html	0.0%	0.0%	→
Trivia	90.0%	90.0%	→
Math	55.0%	55.0%	→
Reasoning	40.0%	40.0%	→
Medical	80.0%	80.0%	→
Linux	45.0%	45.0%	→
Writing	20.0%	20.0%	→

Average: 41.2% -> 41.2% (+0.0%)

Quick Start

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("CompactAI/LFM2.5-1.2B-Instruct-python-safe")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/LFM2.5-1.2B-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))