Instructions to use stevenlearns/caption-tool with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stevenlearns/caption-tool 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="stevenlearns/caption-tool")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stevenlearns/caption-tool", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
README.md
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# Caption Tool
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A small, friendly tool that writes text descriptions (captions) for every image
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license: mit
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tags:
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- image-captioning
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- dataset-tools
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- lora
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- pytorch
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pipeline_tag: image-to-text
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library_name: transformers
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pretty_name: Caption Tool
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---
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# Caption Tool
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A small, friendly tool that writes text descriptions (captions) for every image
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