Instructions to use Thouph/clip-vit-l-224-patch14-datacomp-image-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Thouph/clip-vit-l-224-patch14-datacomp-image-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Thouph/clip-vit-l-224-patch14-datacomp-image-classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoTokenizer, AutoModelForImageClassification tokenizer = AutoTokenizer.from_pretrained("Thouph/clip-vit-l-224-patch14-datacomp-image-classification") model = AutoModelForImageClassification.from_pretrained("Thouph/clip-vit-l-224-patch14-datacomp-image-classification") - Notebooks
- Google Colab
- Kaggle
step 86000
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