abhinav0231/Lily-1.5b-v0.1

Overview

Lily 1.5B v0.1 is a 1.5 billion parameter language model developed by abhinav0231, fine-tuned from the Qwen 2.5 1.5B Instruct base model. Its core differentiator is its explicit chain-of-thought reasoning process, where it first generates step-by-step reasoning within <think> tags, followed by the final, precise answer within <answer> tags. This structured output makes the model's thought process transparent and auditable.

Key Capabilities

• Transparent Reasoning: Provides visible intermediate reasoning steps, enhancing clarity and debuggability.
• Structured Output: Adheres to a consistent <think>...</think><answer>...</answer> format.
• Precision and Directness: Optimized to avoid filler phrases and scale response depth to question complexity.
• General-Purpose Assistance: Functions as a versatile assistant for various tasks.

Ideal Use Cases

• Reasoning and Logic Problems: Effective for tasks requiring structured thought.
• Code Explanation and Generation: Can break down code logic and assist in code creation.
• Structured Question Answering: Delivers precise and organized responses.
• Step-by-Step Problem Solving: Useful in scenarios where the process to the answer is as important as the answer itself.
• Applications requiring Reasoning Transparency: Suitable for grading, debugging, or tutoring where understanding why an answer is given is critical.

Limitations

• Parameter Size: At 1.5B, it is not suited for tasks requiring extensive world knowledge or very long multi-document contexts.
• Language Focus: Primarily trained on English data, limiting multilingual performance.
• No Tool Use: This version does not support function calling or structured tool outputs.