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--- |
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license: mit |
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metrics: |
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- bleu |
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- rouge |
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- meteor |
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- bertscore |
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base_model: |
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- liuhaotian/llava-v1.5-7b |
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pipeline_tag: visual-question-answering |
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--- |
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# visual-qa-tem Model Card |
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## Model details |
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**base_model** |
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We finetune our custom data on LLava-v1.5-7b |
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See on :[liuhaotian/llava-v1.5-7b](https://huggingface.co/liuhaotian/llava-v1.5-7b) |
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**Paper or resources for more information:** |
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Our source code publish on : https://github.com/SmartLab-Roy/visual-qa-tem.git |
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### Download Model |
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```python |
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from huggingface_hub import snapshot_download |
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import os |
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# Download the model to local directory |
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model_path = snapshot_download( |
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repo_id="LabSmart/visual-qa-tem", |
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cache_dir="./models", # Local cache directory |
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resume_download=True |
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) |
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print(f"Model downloaded to: {model_path}") |
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``` |
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### Quick Start |
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Reference [LLaVA](https://github.com/haotian-liu/LLaVA.git) for environment setup and CLI inference: |
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``` |
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python -m llava.serve.cli \ |
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--model-path "model_path from the download output"\ |
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--image-file "path/to/your/tem_image.jpg" \ |
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--load-4bit |
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``` |
