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.

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