tags:

• facebook
• meta
• pytorch
• llama
• llama-3
• mlx
• mlx
• reasoning
• llama
• deepseek
• ollama
• chain-of-thoughts
• small-llm
• edge base_model: mlx-community/Llama-3.2-3B-Instruct language:
• en
• de
• fr
• it
• pt
• hi
• es
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ReasonableLlama-3B: A Fine-Tuned Reasoning Model

HF: https://huggingface.co/adeelahmad/ReasonableLlama3-3B-Jr Ollama: https://ollama.com/adeelahmad/ReasonableLLAMA-Jr-3b

Welcome to ReasonableLlama-3B, a cutting-edge reasoning model built on the foundation of LLaMA-3B. This model has been carefully fine-tuned to enhance its capabilities in logical thinking, problem-solving, and creative analysis.

Overview

• Model Name: ReasonableLlama-3B
• Base Architecture: LLaMA-3B (Large Language Model with 3B parameters)
• Purpose: Designed for tasks requiring advanced reasoning, problem-solving, and creative thinking

Features

• Advanced Reasoning: Excels in logical analysis, problem-solving, and decision-making.
• Creative Thinking: Generates innovative solutions and ideas.
• Curriculum-Based Fine-Tuning: Trained on high-quality datasets to enhance reasoning abilities.

Technical Details

• Parameter Count: 3B parameters
• Training Process: Fine-tuned using state-of-the-art techniques for reasoning tasks
• Specialization: Optimized for specific reasoning workflows and scenarios

Use Cases

• Research: Facilitates complex problem-solving and theoretical analysis.
• Education: Assists in creating educational examples and problem sets.
• Problem Solving: Helps generate innovative solutions across various domains.

Installation and Usage

• Integration: Can be integrated into existing systems via APIs or local setup.
• Inputs: Supports text and images, leveraging Ollama's versatile capabilities.

Limitations

• Scope: Limited to single-step reasoning; multi-hop reasoning is a current focus area.
• Data Bias: Caution with dataset provenance as it may reflect historical biases.

Contributing

Contributions welcome! Fork the project, submit issues, and pull requests on GitHub. Your insights can help shape future improvements.

Citations

• Special thanks to LLaMA's developers for providing a strong foundation.
• Acknowledgments to the community contributing to open-source AI advancements.