Instructions to use Yova/SmallCap7M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yova/SmallCap7M 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="Yova/SmallCap7M")# Load model directly from transformers import SmallCap model = SmallCap.from_pretrained("Yova/SmallCap7M", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload the vizwiz captions
Browse filesThe index captions of vizwiz
- .gitattributes +1 -0
- vizwiz.json +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:a2acac8194e1000bcff2cdefaf4095ad722c291e88c9ea2bfd750e063ebb4ced
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size 11621896
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