Instructions to use Kushalguptaiitb/table_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kushalguptaiitb/table_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Kushalguptaiitb/table_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Kushalguptaiitb/table_test") model = AutoModelForObjectDetection.from_pretrained("Kushalguptaiitb/table_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config_loader.py from Kushalguptaiitb/table_test: direct link, hf CLI and curl.
- Browser
- Download file 173 Bytes
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https://huggingface.co/Kushalguptaiitb/table_test/resolve/main/config_loader.py
- Command line
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hf download hf://Kushalguptaiitb/table_test/config_loader.py
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curl -L -o config_loader.py https://huggingface.co/Kushalguptaiitb/table_test/resolve/main/config_loader.py
173 Bytes
| import yaml | |
| def load_config(config_path: str) -> dict: | |
| """Load configuration from a YAML file.""" | |
| with open(config_path, 'r') as f: | |
| return yaml.safe_load(f) |