Instructions to use shubhamWi91/train65 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train65 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train65")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train65") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train65", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09eb8065bc115c1eadc8c4044d9caca1f4008ad73a2ab5ce1674421de174ecb2
- Size of remote file:
- 4.09 kB
- SHA256:
- 689afae20e2ed5af0351152c8693a852de3f314b8db2e7aa3577b92c8bf9574d
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