README.md

---
library_name: peft
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- lora
- reasoning
- chain-of-thought
- general-purpose
- atlas-labs
---

# Mini-Fable-5-Qwen

This is a general-purpose reasoning model fine-tuned by **Atlas Labs**. It is designed to handle a wide array of tasks—from coding and mathematics to creative writing and world knowledge—using a structured **Chain-of-Thought (CoT)** approach.

## Model Description

Mini-Fable-5-Qwen leverages the power of the Qwen-2.5-1.5B base and has been enhanced with high-quality synthetic reasoning traces. It utilizes a `<thought>` tag to internalize complex logic before providing a final answer, ensuring accuracy across diverse domains.

### Key Features
- **General Purpose:** Trained on instructions covering logic, science, coding, and general world knowledge.
- **Reasoning First:** Native support for step-by-step thinking.
- **Efficiency:** Optimized for fast local CPU inference while maintaining high-tier intelligence.

## How to Use

This is a LoRA adapter. You can load it using the `peft` library with the `Qwen/Qwen2.5-1.5B-Instruct` base model.

```python
from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM, AutoTokenizer

base_model_id = "Qwen/Qwen2.5-1.5B-Instruct"
adapter_id = "Atlas-labs/mini-fable-5-qwen"

model = AutoModelForCausalLM.from_pretrained(base_model_id)
model = PeftModel.from_pretrained(model, adapter_id)
```

## Developed By
**Atlas Labs**