thetmon/c14
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Feb 23, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The thetmon/c14 is a LoRA adapter fine-tuned from the Qwen/Qwen3-4B-Instruct-2507 base model, developed by thetmon. This 4 billion parameter adapter is specifically optimized for multi-turn agent task performance, excelling in environments like ALFWorld for household tasks and DBBench for database operations. It enhances the base model's ability to handle environment observation, action selection, tool use, and error recovery in complex, multi-step scenarios.
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Overview
This repository provides a LoRA adapter (r=64, alpha=128) fine-tuned by thetmon from the Qwen/Qwen3-4B-Instruct-2507 base model using LoRA + Unsloth. It contains only the adapter weights, requiring the base model to be loaded separately.
Key Capabilities
- Multi-turn Agent Task Performance: Specifically trained to improve performance in complex, multi-step agent tasks.
- Environment Interaction: Learns to process environment observations and select appropriate actions.
- Tool Use: Enhanced capabilities for integrating and utilizing tools within task trajectories.
- Error Recovery: Designed to improve the model's ability to recover from errors during multi-turn interactions.
Training Details
- Base Model: Qwen/Qwen3-4B-Instruct-2507
- Method: LoRA (full precision base)
- Max Sequence Length: 4096 tokens
- Epochs: 3
- Learning Rate: 2e-04
- Training Data: Utilizes u-10bei/sft_alfworld_trajectory_dataset_v5 and u-10bei/dbbench_sft_dataset_react_v4, both under the MIT License.
Good For
- Agentic Workflows: Ideal for applications requiring an AI agent to perform sequential tasks.
- ALFWorld Tasks: Excels in household task automation scenarios.
- DBBench Operations: Suited for database interaction and operation tasks.