CooperBench/qwen3.5-9b-tool-use-sft-merged
CooperBench/qwen3.5-9b-tool-use-sft-merged is a 9 billion parameter language model developed by CooperBench, fine-tuned for tool-use capabilities. With a substantial context length of 32768 tokens, this model is designed to excel in scenarios requiring interaction with external tools and APIs. Its primary strength lies in facilitating complex task execution through function calling and structured output generation, making it suitable for advanced automation and agent-based applications.
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Model Overview
CooperBench/qwen3.5-9b-tool-use-sft-merged is a 9 billion parameter language model, developed by CooperBench, specifically fine-tuned for tool-use applications. It features a significant context window of 32768 tokens, enabling it to process extensive inputs and maintain complex conversational states.
Key Capabilities
- Tool-Use Optimization: This model is specialized for scenarios where an LLM needs to interact with external tools, APIs, or functions to complete tasks.
- Extended Context Length: A 32768-token context window supports handling long conversations, detailed instructions, and multi-step reasoning processes.
- Task Automation: Designed to facilitate advanced automation workflows by interpreting user requests and orchestrating tool calls.
Good For
- Agentic Workflows: Ideal for building AI agents that can perform actions by calling external functions.
- Complex Problem Solving: Suitable for tasks requiring multiple steps, external data retrieval, or interaction with various systems.
- Structured Output Generation: Excels in generating outputs that conform to specific formats required for tool invocation or data processing.