Instructions to use giladvdn/test-sam-handler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giladvdn/test-sam-handler with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="giladvdn/test-sam-handler")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("giladvdn/test-sam-handler") model = AutoModelForMaskGeneration.from_pretrained("giladvdn/test-sam-handler") - Notebooks
- Google Colab
- Kaggle
| import base64 | |
| from handler import EndpointHandler | |
| my_handler = EndpointHandler(path=".") | |
| image = base64.b64encode(open("../sam-vit-huge/car.png", "rb").read()) | |
| input = {"image": image, "points": [[450, 600]]} | |
| result = my_handler(input) | |
| print(result) | |