Instructions to use Salesforce/blip2-itm-vit-g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip2-itm-vit-g with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Salesforce/blip2-itm-vit-g") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("Salesforce/blip2-itm-vit-g") model = AutoModelForZeroShotImageClassification.from_pretrained("Salesforce/blip2-itm-vit-g") - Notebooks
- Google Colab
- Kaggle
Can Blip2ForImageTextRetrieval be trained with Trainer?
#5
by wang-sy - opened
In the definition of Blip2ImageTextMatchingModelOutput, loss was defined as
Args:
loss (`torch.FloatTensor` of shape `(1,)`, *optional*, returned when `return_loss` is `True`):
Contrastive loss for image-text similarity.
However the calculation of loss was not done in the forward loop of Blip2ForImageTextRetrieval, am I missing out on this calculation, where is loss calculated?
Is the training of Blip2ForImageTextRetrievalsupported by the Trainer?
Thank you for the great work!