durgasai299792458/Qwen3.5-4B-Agent-Finetune

VISIONConcurrency Cost:1Model Size:4.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jun 13, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The durgasai299792458/Qwen3.5-4B-Agent-Finetune is a 4.5 billion parameter language model, finetuned by durgasai299792458 from the unsloth/Qwen3.5-4B base model. It features a 32768 token context length and was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for agent-based applications, leveraging its finetuned capabilities for specific task execution.

Loading preview...

Model Overview

The durgasai299792458/Qwen3.5-4B-Agent-Finetune is a 4.5 billion parameter language model, developed by durgasai299792458. It is finetuned from the unsloth/Qwen3.5-4B base model and operates under an Apache-2.0 license. The model boasts a substantial context length of 32768 tokens, making it suitable for processing longer sequences of text.

Key Characteristics

  • Base Model: Finetuned from unsloth/Qwen3.5-4B.
  • Training Efficiency: Leverages Unsloth and Huggingface's TRL library for 2x faster training.
  • Parameter Count: 4.5 billion parameters.
  • Context Length: Supports a 32768 token context window.

Intended Use Cases

This model is specifically finetuned for agent-based applications, suggesting its strength lies in tasks requiring sequential decision-making, tool use, or interactive problem-solving. Its efficient training process and substantial context window make it a candidate for scenarios where rapid iteration and handling complex instructions are beneficial.

Finetunes
1 models