Instructions to use SvNext/GambleStrTestYOLO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SvNext/GambleStrTestYOLO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SvNext/GambleStrTestYOLO")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SvNext/GambleStrTestYOLO") model = AutoModelForObjectDetection.from_pretrained("SvNext/GambleStrTestYOLO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b499d537f5333fb00c8da02608c7d919a2b67a4c2f6c6ba851869be1f6b6ec5
- Size of remote file:
- 25.9 MB
- SHA256:
- 76c429673476247d94477f0952f828b6814cf4c04cf416dba13b28a92806896b
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