Instructions to use as-cle-bert/bcus-class-segformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use as-cle-bert/bcus-class-segformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="as-cle-bert/bcus-class-segformer") 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("as-cle-bert/bcus-class-segformer") model = AutoModelForImageClassification.from_pretrained("as-cle-bert/bcus-class-segformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - autotrain | |
| - image-classification | |
| widget: | |
| - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg | |
| example_title: Tiger | |
| - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg | |
| example_title: Teapot | |
| - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg | |
| example_title: Palace | |
| datasets: | |
| - as-cle-bert/breastcanc-ultrasound-class | |
| # Model Trained Using AutoTrain | |
| - Problem type: Image Classification | |
| ## Validation Metrics | |
| No validation metrics available | |