Supreeth/verirl-sft-qwen3-4b-tooluse-merged
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Apr 26, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
Supreeth/verirl-sft-qwen3-4b-tooluse-merged is a 4 billion parameter Qwen3-based language model developed by Supreeth, fine-tuned from unsloth/qwen3-4b-thinking-2507-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. Its primary characteristic is its optimization for tool use, making it suitable for applications requiring external function calls or structured interactions.
Loading preview...
Supreeth/verirl-sft-qwen3-4b-tooluse-merged Overview
This model is a 4 billion parameter Qwen3-based language model developed by Supreeth, specifically fine-tuned for tool use capabilities. It was built upon the unsloth/qwen3-4b-thinking-2507-unsloth-bnb-4bit base model.
Key Capabilities
- Enhanced Tool Use: Optimized for scenarios requiring the model to interact with external tools or APIs, enabling more complex and structured problem-solving.
- Efficient Training: Leverages Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Qwen3 Architecture: Benefits from the foundational strengths of the Qwen3 architecture, providing a robust base for its specialized fine-tuning.
Good for
- Agentic Workflows: Ideal for developing AI agents that need to perform actions by calling external functions or using specific tools.
- Structured Interactions: Suitable for applications where the model needs to generate structured outputs or follow specific protocols for interaction.
- Rapid Prototyping: The efficient training methodology makes it a good candidate for projects requiring quick iteration and deployment of tool-using LLMs.