Instructions to use ProbeX/Model-J__ResNet__model_idx_0338 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_0338 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_0338") 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_0338") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0338", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
60b5bf6 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:08388562836391b0346eea2640a7e10edc98704de4ce91aeec0f836d97fb7be6
size 5368
|