Instructions to use hf-tiny-model-private/tiny-random-DetaForObjectDetection 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-DetaForObjectDetection 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-DetaForObjectDetection")# Load model directly from transformers import AutoModelForObjectDetection model = AutoModelForObjectDetection.from_pretrained("hf-tiny-model-private/tiny-random-DetaForObjectDetection", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdfc9a15c4169f73441dcecca775a7498d46da39132f43dd116c90d826acad63
- Size of remote file:
- 124 MB
- SHA256:
- 7b100f215dd66c4b7ffcd91818f9686862190fed22c806bebaaa1367312ee8d4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.