Instructions to use mthandazo/output-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mthandazo/output-models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mthandazo/output-models") 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("mthandazo/output-models") model = AutoModelForImageClassification.from_pretrained("mthandazo/output-models") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("mthandazo/output-models")
model = AutoModelForImageClassification.from_pretrained("mthandazo/output-models")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mthandazo/output-models") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")