Instructions to use noamrot/FuseCap_Image_Captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noamrot/FuseCap_Image_Captioning with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="noamrot/FuseCap_Image_Captioning")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("noamrot/FuseCap_Image_Captioning") model = AutoModelForImageTextToText.from_pretrained("noamrot/FuseCap_Image_Captioning") - Notebooks
- Google Colab
- Kaggle
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README.md
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``` Citation
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@article{rotstein2023fusecap,
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}
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```
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``` Citation
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@article{rotstein2023fusecap,
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title={FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions},
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author={Noam Rotstein and David Bensaid and Shaked Brody and Roy Ganz and Ron Kimmel},
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year={2023},
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eprint={2305.17718},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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