Instructions to use hf-internal-testing/tiny-random-TableTransformerForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TableTransformerForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-internal-testing/tiny-random-TableTransformerForObjectDetection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-TableTransformerForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-internal-testing/tiny-random-TableTransformerForObjectDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eada2f8365379b7b2f2a621d6e81a4b4e80e9ad4900beec13c3f7cd1c6b8826c
- Size of remote file:
- 103 MB
- SHA256:
- 447785c9d09b8630ec9abb1ec2b19fa5ee26de4d82effd7e46195918261b0bc1
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