Instructions to use michelecafagna26/blip-base-captioning-ft-hl-narratives 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-narratives 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-narratives")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("michelecafagna26/blip-base-captioning-ft-hl-narratives") model = AutoModelForMultimodalLM.from_pretrained("michelecafagna26/blip-base-captioning-ft-hl-narratives", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 380bc1a505ae8adb77a7319e1f105e260dd7914fb4153c32f25b9d90390c1df8
- Size of remote file:
- 990 MB
- SHA256:
- 9846aa27f2554ddac64c51266e09b36fb7cd4720639417d1d822b43dc95a827b
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