Instructions to use unni12345/MedBlip2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unni12345/MedBlip2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="unni12345/MedBlip2")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("unni12345/MedBlip2") model = AutoModelForMultimodalLM.from_pretrained("unni12345/MedBlip2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 129baf6bf6064c66bc1fb23d50692db088a90a8e68e74b29941516927dfa4e3b
- Size of remote file:
- 9.96 GB
- SHA256:
- afd75d770791bbae41fff3d03ec5da6dcbb4bc984756d197773e9bc40fdb1e84
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