Instructions to use hf-internal-testing/tiny-random-OwlViTForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-OwlViTForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="hf-internal-testing/tiny-random-OwlViTForObjectDetection")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-OwlViTForObjectDetection") model = AutoModelForZeroShotObjectDetection.from_pretrained("hf-internal-testing/tiny-random-OwlViTForObjectDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-OwlViTForObjectDetection: direct link, hf CLI and curl.
- Browser
- Download file 1.56 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-OwlViTForObjectDetection/resolve/refs%2Fpr%2F3/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-OwlViTForObjectDetection@refs/pr/3/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-OwlViTForObjectDetection/resolve/refs%2Fpr%2F3/model.safetensors
1.56 MB
- Xet hash:
- 325d6ab043a46f34369dd48dff1c302b12f0c83f471b08aa4ac07a5d000314d9
- Size of remote file:
- 1.56 MB
- SHA256:
- f5a139b659a9d7fd3b08a425d1922f0af93ad012d075f44eb691df689a6ddf2c
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