Instructions to use Junhoee/BLIP-FT-VET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Junhoee/BLIP-FT-VET 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="Junhoee/BLIP-FT-VET")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("Junhoee/BLIP-FT-VET") model = AutoModelForImageTextToText.from_pretrained("Junhoee/BLIP-FT-VET") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04630b1724085967aed983bf5366bb170ad47f0e59778ebba37e15317c224052
- Size of remote file:
- 5.24 kB
- SHA256:
- dd641e7f06f7e026149f25bec402b83a5823c6de5813bb6720448aa3111f5bc5
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