---
base_model: LiquidAI/LFM2.5-1.2B-Thinking
library_name: transformers
model_name: LFM2.5-1.2B-Thinking-CodeX
tags:
- generated_from_trainer
- sft
- trl
licence: license
datasets:
- Modotte/CodeX-2M-Thinking
license: apache-2.0
---

<div align="center">
    <img src="https://cdn-uploads.huggingface.co/production/uploads/6615494716917dfdc645c44e/k5xrb5inTiff6dFC1A8UN.png" alt="Liquid CodeX" style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em; reading-order: 20px; border-radius: 20px;"/>
</div>

# LFM2.5-1.2B-Thinking-CodeX (Liquid CodeX)
LFM2.5-1.2B-Thinking-CodeX (Liquid CodeX) is a distillation of Claude into LFM2.5-1.2B-Thinking via LoRA.

# Benchmark

|Model                                    |Average|HellaSwag|MMLU |Piqa |Source|
|-----------------------------------------|-------|---------|-----|-----|------|
|FlameFOX/LFM2.5-1.2B-Distilled-Claude-4.6|46.76  |39.51    |31.99|68.77|[Intel/low bit open llm leaderboard](https://huggingface.co/spaces/Intel/low_bit_open_llm_leaderboard)|
|FlameFOX/LFM2.5-1.2B-Thinking-CodeX      |45.25  |39.70    |26.56|69.48|As the one from above|

## Quick start

```python
from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="FlameF0X/LFM2.5-1.2B-Thinking-CodeX", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```

## Training procedure

 



This model was trained with SFT.

### Framework versions

- TRL: 1.2.0
- Transformers: 5.0.0
- Pytorch: 2.10.0+cu128
- Datasets: 4.8.4
- Tokenizers: 0.22.2

## Citations



Cite TRL as:
    
```bibtex
@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}
```