mini-Cogito-R1
| Property | Value |
|---|---|
| Developer | Daemontatox |
| Parameter Count | 1.5B |
| Base Model | unsloth/deepscaler-1.5b-preview |
| License | Apache-2.0 |
| Model URL | https://huggingface.co/Daemontatox/mini-Cogito-R1 |
What is mini-Cogito-R1?
mini-Cogito-R1 is a lightweight language model specifically designed for edge computing applications, combining efficient performance with robust mathematical reasoning and text generation capabilities. Developed by Daemontatox, this model leverages the Unsloth framework and Huggingface's TRL library to achieve 2x faster training speeds while maintaining high performance standards.
Implementation Details
The model is built upon the unsloth/deepscaler-1.5b-preview architecture and has been fine-tuned using multiple high-quality datasets including NuminaMath-QwQ-CoT-5M, GSM8K, and Dolphin-R1. The implementation utilizes 4-bit quantization and optimized training pipelines to ensure efficient deployment on resource-constrained devices.
- Efficient edge device optimization
- 2x faster training using Unsloth framework
- 4-bit quantization for reduced memory footprint
- Specialized mathematical reasoning capabilities
- High-quality text generation features
Core Capabilities
- Mathematical problem-solving and logical reasoning
- Edge computing deployment optimization
- Educational assistance and tutoring
- Content generation for various applications
- Research and experimentation support
Frequently Asked Questions
Q: What makes this model unique?
mini-Cogito-R1 stands out for its optimization for edge devices while maintaining strong mathematical reasoning capabilities. The combination of Unsloth framework implementation and efficient training makes it particularly suitable for resource-constrained environments without compromising on performance.
Q: What are the recommended use cases?
The model excels in educational applications, particularly for mathematical problem-solving, content creation, and edge computing deployments. It's ideal for scenarios requiring real-time text generation and reasoning tasks on resource-limited devices.
