thetmon/c5
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Feb 19, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The thetmon/c5 is a 4 billion parameter LoRA adapter fine-tuned from Qwen/Qwen3-4B-Instruct-2507, designed to enhance multi-turn agent task performance. It specializes in improving capabilities for household tasks (ALFWorld) and database operations (DBBench) by learning from full multi-turn trajectories. This adapter focuses on environment observation, action selection, tool use, and error recovery, making it suitable for complex agentic workflows.
Loading preview...
Qwen3-4B ALFWorld+DBBench Mixed LoRA Adapter
This repository provides a LoRA adapter (r=64, alpha=128) fine-tuned from the Qwen/Qwen3-4B-Instruct-2507 base model. It is specifically designed to improve the base model's performance on complex, multi-turn agent tasks.
Key Capabilities
- Enhanced Multi-Turn Agent Performance: Optimized for tasks requiring sequential decision-making and interaction.
- Specialized for ALFWorld: Improves the model's ability to handle household tasks, including environment observation and action selection.
- Specialized for DBBench: Enhances performance in database operation tasks, including tool use and error recovery.
- Trajectory-Based Learning: Loss is applied to all assistant turns in a multi-turn trajectory, allowing the model to learn from complete interaction sequences.
Good For
- Developing agents that need to perform complex, multi-step tasks in simulated environments.
- Applications requiring improved tool use and error recovery in agentic workflows.
- Researchers and developers working on AI agents for household automation or database interaction.
- Extending the capabilities of the Qwen3-4B-Instruct-2507 base model for specific agentic use cases.