Instructions to use Salesforce/blip-vqa-capfilt-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip-vqa-capfilt-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="Salesforce/blip-vqa-capfilt-large")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("Salesforce/blip-vqa-capfilt-large") model = AutoModelForVisualQuestionAnswering.from_pretrained("Salesforce/blip-vqa-capfilt-large") - Notebooks
- Google Colab
- Kaggle
How to send inference request to deployed end point
#11
by AkiraKuniyoshi - opened
Hello, I deployed the model in a serverless Sagemaker end point. However, I can't find the documentation on what should i send and in which format to the model so i can get an inference. Which data structure? and does it make the pre processing in the deployed model? or do i need still to load the processors and pre process the image and tex?
Help will be much appreciated. Thank you!