Instructions to use nnpy/blip-image-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nnpy/blip-image-captioning 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="nnpy/blip-image-captioning")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("nnpy/blip-image-captioning") model = AutoModelForImageTextToText.from_pretrained("nnpy/blip-image-captioning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5f16e7a85b4c3c0e3fd98b46e2634320ba11ddc840552621c7bb4fdcf1979d3
- Size of remote file:
- 990 MB
- SHA256:
- 53831cae9ed807f34df347f32b431d45ca72481636d6f1b852b5021151d85da2
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