Instructions to use ProbeX/Model-J__ResNet__model_idx_0988 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_0988 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_0988") 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_0988") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0988", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
6ec4108 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:78681a10ca90334f077fae9e4f15923f78213c44d66eb332b06a4e4b8f00241c
size 170916120
|