Instructions to use michelecafagna26/blip-base-captioning-ft-hl-actions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michelecafagna26/blip-base-captioning-ft-hl-actions 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="michelecafagna26/blip-base-captioning-ft-hl-actions")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("michelecafagna26/blip-base-captioning-ft-hl-actions") model = AutoModelForImageTextToText.from_pretrained("michelecafagna26/blip-base-captioning-ft-hl-actions") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 888c3401251e8d9efcf2e1e34743123cda952257aebbbbf865b09eed0cc65cee
- Size of remote file:
- 990 MB
- SHA256:
- ce48b3138434cf68609a6ff092a7d55f91d953c10fbe05d0a3dff8f3266e75c5
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