Instructions to use howdyaendra/xblock-base-patch1-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use howdyaendra/xblock-base-patch1-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="howdyaendra/xblock-base-patch1-224") 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("howdyaendra/xblock-base-patch1-224") model = AutoModelForImageClassification.from_pretrained("howdyaendra/xblock-base-patch1-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
327ffdb | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:be321081e73ffc6cae63799360a414dee56067b5572ebec02c8d8764fa8bed69
size 4920
|