iNCurrO/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 iNCurrO/toolcalling-merged-demo is a 2 billion parameter Qwen3-based causal language model developed by iNCurrO. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language tasks, leveraging its Qwen3 architecture for efficient processing.

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Overview

The iNCurrO/toolcalling-merged-demo is a 2 billion parameter language model developed by iNCurrO. It is based on the Qwen3 architecture and was fine-tuned from unsloth/Qwen3-1.7B-unsloth-bnb-4bit. The fine-tuning process utilized Unsloth and Huggingface's TRL library, which facilitated a 2x faster training speed.

Key Characteristics

  • Architecture: Qwen3-based causal language model.
  • Parameter Count: 2 billion parameters.
  • Training Efficiency: Fine-tuned with Unsloth and Huggingface TRL for accelerated training.
  • Context Length: Supports a context length of 32768 tokens.

Potential Use Cases

This model is suitable for a variety of general language understanding and generation tasks, benefiting from its efficient training and Qwen3 foundation. Its 2 billion parameter size makes it a good candidate for applications requiring a balance between performance and computational resources.