Instructions to use ProbeX/Model-J__ResNet__model_idx_0618 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__ResNet__model_idx_0618 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__ResNet__model_idx_0618") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0618") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0618") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 393d01f1549bdce5c6e9366cadb18006d6c62f42a3aa15dc74b56d1207b93c96
- Size of remote file:
- 5.37 kB
- SHA256:
- 6a45bdb7b4fd74d4013069eddee47a2b13ae5fc998b425caa0901979e859152f
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