tnkchaseme/qwen-vl-4b-CROHME
VISIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Apr 23, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The tnkchaseme/qwen-vl-4b-CROHME is a 4 billion parameter Qwen3-VL model developed by tnkchaseme, fine-tuned from unsloth/qwen3-vl-4b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general text generation inference tasks, leveraging its Qwen3-VL architecture for potential multimodal capabilities.
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Model Overview
The tnkchaseme/qwen-vl-4b-CROHME is a 4 billion parameter model developed by tnkchaseme, based on the Qwen3-VL architecture. It was fine-tuned from unsloth/qwen3-vl-4b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Qwen3-VL, indicating potential for multimodal (vision-language) tasks.
- Parameter Count: 4 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: The model was trained 2x faster using Unsloth and Huggingface's TRL library, highlighting an optimized training process.
- License: Released under the Apache-2.0 license, allowing for broad use and distribution.
Potential Use Cases
- Text Generation Inference: Suitable for various text generation tasks, leveraging its instruction-tuned base.
- Multimodal Applications: Given its Qwen3-VL base, it may be applicable to tasks involving both visual and textual inputs, though specific multimodal capabilities are not detailed in the provided README.
- Efficient Deployment: The optimized training with Unsloth suggests it might be well-suited for scenarios requiring efficient fine-tuning and deployment.