Instructions to use hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection: direct link, hf CLI and curl.
- Browser
- Download file 107 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-ConditionalDetrForObjectDetection/resolve/refs%2Fpr%2F1/model.safetensors
107 MB
- Xet hash:
- 637410702de000e001a673e6c29e568e410d10eab14d6dd9e68d4d1f7b4cd675
- Size of remote file:
- 107 MB
- SHA256:
- fe06544a4231e7e0fcce5de485f0e1914e5d84cd0f7cf0722e7ba82cb1a34094
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