LFM2.5-1.2B-Thinking
Collection
Pruned models based on LiquidAI/LFM2.5-1.2B-Thinking
β’
17 items
β’
Updated
MATH-optimized | Safe pruning | 30% weights pruned
This model is a conservatively pruned version of LiquidAI/LFM2.5-1.2B-Thinking.
Note: Minimal quality drop detected. The Wanda pruning algorithm effectively identifies and removes less important weights while preserving model capability.
| Category | Original | Pruned | Change |
|---|---|---|---|
| Python | 0.0% | 0.0% | β |
| Html | 0.0% | 0.0% | β |
| Trivia | 35.0% | 30.0% | β 5.0% |
| Math | 15.0% | 10.0% β | β 5.0% |
| Reasoning | 35.0% | 30.0% | β 5.0% |
| Medical | 50.0% | 50.0% | β |
| Linux | 5.0% | 15.0% | β 10.0% |
| Writing | 45.0% | 40.0% | β 5.0% |
Average: 23.1% -> 21.9% (-1.2%)
Math Retention: 66.7%
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("CompactAI/LFM2.5-1.2B-Thinking-math-safe")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/LFM2.5-1.2B-Thinking-math-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))
| Property | Value |
|---|---|
| Base Model | LiquidAI/LFM2.5-1.2B-Thinking |
| Specialization | Math |
| Prune Mode | Safe |
| Weight Reduction | 30% weights pruned |
This model inherits the license from the base model.
Base model
LiquidAI/LFM2.5-1.2B-Base