AutoSurferForCopilot/RedditQwen3.5ToolFtPoc
RedditQwen3.5ToolFtPoc is a 9 billion parameter language model developed by AutoSurferForCopilot, fine-tuned from Qwen3.5-9B. This model is specifically optimized for tool-use capabilities, leveraging the actionengine_trajectories dataset. It features a substantial 32,768 token context length, making it suitable for complex tasks requiring extensive contextual understanding and interaction with external tools.
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Model Overview
RedditQwen3.5ToolFtPoc is a 9 billion parameter language model, fine-tuned by AutoSurferForCopilot from the base Qwen3.5-9B architecture. This model is specifically designed for enhanced tool-use functionality, having been trained on the actionengine_trajectories dataset. It supports a significant context length of 32,768 tokens, enabling it to process and understand lengthy inputs for complex tasks.
Key Capabilities
- Tool-Use Optimization: Fine-tuned on
actionengine_trajectoriesfor improved interaction with external tools and action execution. - Large Context Window: Benefits from a 32,768 token context length, allowing for deep contextual understanding and handling of extensive information.
- Qwen3.5 Base: Leverages the robust capabilities of the Qwen3.5-9B model as its foundation.
Training Details
The model was trained with a learning rate of 1e-05, using an AdamW optimizer with specific beta and epsilon values. Training involved a total batch size of 8 across 4 devices, with 2 gradient accumulation steps, for 3 epochs. A cosine learning rate scheduler was employed with 0.1 warmup steps.
Intended Uses
This model is particularly well-suited for applications requiring sophisticated tool interaction, such as automated agents, complex task execution, and scenarios where a large context window is crucial for understanding user intent and external system states.