OpenHands LM 1.5B
| Property | Value |
|---|---|
| Parameter Count | 1.5 Billion |
| Model Type | Language Model for Software Development |
| Hugging Face | all-hands/openhands-lm-1.5b-v0.1 |
| Context Window | 128K tokens |
What is openhands-lm-1.5b-v0.1?
OpenHands LM 1.5B is a compact version of the larger 32B model, specifically designed for speculative decoding in software development tasks. It follows the same training methodology as its larger counterpart but in a more accessible form factor for developers with limited computational resources.
Implementation Details
The model is built using specialized fine-tuning processes leveraging training data generated by OpenHands itself on diverse open-source repositories. It implements an RL-based framework as outlined in SWE-Gym, creating training environments and utilizing successful resolutions for model improvement.
- 128K token context window for handling large codebases
- Optimized for local deployment and speculative decoding
- Built on proven software development training methodologies
Core Capabilities
- Software issue resolution and code generation
- GitHub integration capabilities
- Local deployment compatibility
- Optimized for resource-efficient operation
Frequently Asked Questions
Q: What makes this model unique?
This model offers a balance between performance and resource requirements, making it accessible for local deployment while maintaining core capabilities for software development tasks. It's specifically optimized for speculative decoding, making it efficient for real-world applications.
Q: What are the recommended use cases?
The model is best suited for software development tasks, particularly GitHub issue resolution and code generation. It's designed to be integrated into development workflows and can be run locally, making it ideal for developers who need AI assistance without relying on external APIs.
