golgat/toolcalling-merged-demo

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:2BQuant:BF16Ctx Length:32kPublished:Apr 2, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

The golgat/toolcalling-merged-demo is a 2 billion parameter Qwen3-based model developed by golgat, fine-tuned from unsloth/Qwen3-1.7B-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging its efficient fine-tuning process.

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Model Overview

The golgat/toolcalling-merged-demo is a 2 billion parameter language model based on the Qwen3 architecture, developed by golgat. It was fine-tuned from the unsloth/Qwen3-1.7B-unsloth-bnb-4bit model, indicating a focus on efficient training and deployment.

Key Characteristics

  • Architecture: Qwen3-based, a robust and capable large language model family.
  • Parameter Count: 2 billion parameters, offering a balance between performance and computational efficiency.
  • Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
  • License: Released under the Apache-2.0 license, allowing for broad use and distribution.

Potential Use Cases

This model is suitable for a variety of general language understanding and generation tasks where a moderately sized, efficiently trained model is beneficial. Its Qwen3 foundation suggests capabilities in areas such as:

  • Text generation and completion.
  • Question answering.
  • Summarization.
  • Basic conversational AI.