Instructions to use dokutoshi/owlvit-base-patch32_FT_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dokutoshi/owlvit-base-patch32_FT_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="dokutoshi/owlvit-base-patch32_FT_cppe5")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("dokutoshi/owlvit-base-patch32_FT_cppe5") model = AutoModelForZeroShotObjectDetection.from_pretrained("dokutoshi/owlvit-base-patch32_FT_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dokutoshi/owlvit-base-patch32_FT_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 2.22 MB
-
https://huggingface.co/dokutoshi/owlvit-base-patch32_FT_cppe5/resolve/main/tokenizer.json
- Command line
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hf download hf://dokutoshi/owlvit-base-patch32_FT_cppe5/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/dokutoshi/owlvit-base-patch32_FT_cppe5/resolve/main/tokenizer.json
2.22 MB
File too large to display, you can check the raw version instead.