LFM2.5-1.2B-Thinking
Collection
Collection of pruned models based on LiquidAI/LFM2.5-1.2B-Thinking
β’
55 items
β’
Updated
π― REASONING-optimized | π¦ Medium pruning | β‘ 20% weights pruned
This model is a moderately pruned version of LiquidAI/LFM2.5-1.2B-Thinking, specialized for REASONING tasks using activation-aware weight pruning (Wanda-style).
| Category | Original | Pruned | Change |
|---|---|---|---|
| Python | 0.0% | 0.0% | β |
| Html | 0.0% | 0.0% | β |
| Trivia | 93.3% | 93.3% | β |
| Math | 100.0% | 100.0% | β |
| Reasoning | N/A | N/A | |
| Medical | 86.7% | 73.3% | β 13.3% |
| Linux | 86.7% | 86.7% | β |
| Writing | 60.0% | 66.7% | β 6.7% |
Average: 61.0% β 60.0% (-1.0%)
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("CompactAI/LFM2.5-1.2B-Thinking-reasoning-medium")
tokenizer = AutoTokenizer.from_pretrained("CompactAI/LFM2.5-1.2B-Thinking-reasoning-medium")
# Example usage
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 | Reasoning |
| Prune Mode | Medium |
| Pruning Method | Activation-based weight pruning (Wanda) |
| Weight Reduction | 20% weights pruned |
This model is part of the LFM2.5-1.2B-Thinking pruned model collection. Other variants:
This model inherits the license from the base model LiquidAI/LFM2.5-1.2B-Thinking.
Generated by ZANNPS [Zeto Automatic Neural Network Pruning System]
Base model
LiquidAI/LFM2.5-1.2B-Base