Instructions to use Salesforce/blip2-itm-vit-g-coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip2-itm-vit-g-coco 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-coco") 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-coco") model = AutoModelForZeroShotImageClassification.from_pretrained("Salesforce/blip2-itm-vit-g-coco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93f57a488e9d7d95e066a7d37d8087bbc24b09bb3a77a2789569fe7016af77c0
- Size of remote file:
- 4.79 GB
- SHA256:
- e2a1696f11b18400dcfb98c896f9864b47dd3fc3dd1e28676eefc4b7c80e43f2
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