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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - leon-se/ForestFireInsights-Eval
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+ language:
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+ - en
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+ base_model:
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+ - Qwen/Qwen2.5-VL-7B-Instruct
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+ tags:
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+ - climate
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+ ---
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+
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+ # Model Card: ForestFireVLM-7B-FP8-Dynamic
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+
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+ ## Model Description
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+ ForestFireVLM-7B is a specialized vision-language model fine-tuned from [Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) specifically for forest fire detection and analysis tasks. This model is designed to identify and analyze various aspects of forest fires from aerial imagery, including smoke detection, flame visibility, fire characteristics, and potential hazards.
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+ The [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory/) framework was used for fine-tuning this model. Quantized to FP8 with `llm-compressor`.
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+
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+ ## How to Use
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+ The model can be used with vLLM to create an OpenAI API compatible endpoint:
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+
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+ ```bash
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+ vllm serve leon-se/ForestFireVLM-7B-FP8-Dynamic --max-model-len 10000
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+ ```
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+
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+ ## Evaluations
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+ Evaluations were done with our code available on [GitHub](https://github.com/leon-seidel/ForestFireVLM), using the [ForestFireInsights-Eval](https://huggingface.co/datasets/leon-se/ForestFireInsights-Eval) dataset.
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+
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+ ## Citations
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+
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+ This model is associated with research currently under peer review with MDPI. Please cite our paper when using this model:
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+
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+ ```
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+ [Citation will be added when the paper is published]
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+ ```