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 # Warning: Pipeline type "visual-question-answering" 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("visual-question-answering", model="unni12345/MedBlip2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("unni12345/MedBlip2") model = AutoModelForMultimodalLM.from_pretrained("unni12345/MedBlip2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM
processor = AutoProcessor.from_pretrained("unni12345/MedBlip2")
model = AutoModelForMultimodalLM.from_pretrained("unni12345/MedBlip2", device_map="auto")Quick Links
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# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" 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("visual-question-answering", model="unni12345/MedBlip2")