Instructions to use ProbeX/Model-J__ResNet__model_idx_0324 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_0324 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_0324") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0324") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0324", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ProbeX/Model-J__ResNet__model_idx_0324: direct link, hf CLI and curl.
- Browser
- Download file 171 MB
-
https://huggingface.co/ProbeX/Model-J__ResNet__model_idx_0324/resolve/main/model.safetensors
- Command line
-
hf download hf://ProbeX/Model-J__ResNet__model_idx_0324/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ProbeX/Model-J__ResNet__model_idx_0324/resolve/main/model.safetensors
171 MB
- Xet hash:
- 416c611718f55fd444507b2b08a663ecf0e620252a22b4613b6d709e64e810cb
- Size of remote file:
- 171 MB
- SHA256:
- 87a7a32fd173cc94dd2d2aed6a744ff2c8a15aa5a9fa988cd115881e8b56666c
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