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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from hf-internal-testing/tiny-random-TableTransformerForObjectDetection: direct link, hf CLI and curl.
- Browser
- Download file 103 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-TableTransformerForObjectDetection/resolve/9cf1e3f5c3555a727672a32b49f8b96c5aa20be6/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-TableTransformerForObjectDetection@9cf1e3f5c3555a727672a32b49f8b96c5aa20be6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-TableTransformerForObjectDetection/resolve/9cf1e3f5c3555a727672a32b49f8b96c5aa20be6/pytorch_model.bin
103 MB
- Xet hash:
- 81dec14e0c00cc665180f20a5a224ce04529cdc1f0b291bbc04799f4111198ca
- Size of remote file:
- 103 MB
- SHA256:
- f6edfaadb432cbc95ce047582f1be34f34778c2253556b7e1aa5fabf45499e0c
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