dragonstorm123/qwen3.5-4b-sft-disambiguation
VISIONConcurrent Unit Cost:1Model Size:4.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 9, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold
The dragonstorm123/qwen3.5-4b-sft-disambiguation is a 4.5 billion parameter Qwen3.5 model developed by dragonstorm123. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging its Qwen3.5 base architecture.
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Model Overview
The dragonstorm123/qwen3.5-4b-sft-disambiguation is a 4.5 billion parameter language model, fine-tuned by dragonstorm123. It is based on the Qwen3.5-4B architecture and was developed with a focus on efficient training.
Key Characteristics
- Base Model: Qwen3.5-4B, providing a robust foundation for various language understanding and generation tasks.
- Efficient Training: The model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Parameter Count: Features 4.5 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a context length of 32768 tokens, enabling processing of longer inputs.
Potential Use Cases
This model is suitable for applications requiring a capable language model with a focus on efficient development and deployment. Its Qwen3.5 base makes it versatile for tasks such as:
- Text generation
- Summarization
- Question answering
- General conversational AI