Instructions to use adityarajkishan/ImageCaptioningTransformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adityarajkishan/ImageCaptioningTransformers 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="adityarajkishan/ImageCaptioningTransformers")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("adityarajkishan/ImageCaptioningTransformers") model = AutoModelForImageTextToText.from_pretrained("adityarajkishan/ImageCaptioningTransformers") - Notebooks
- Google Colab
- Kaggle
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README.md
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license: apache-2.0
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tags:
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- image-to-text
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- image-captioning
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license: apache-2.0
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widget:
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
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example_title: Savanna
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
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example_title: Football Match
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/airport.jpg
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example_title: Airport
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