Instructions to use aradootle/sam-vit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aradootle/sam-vit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="aradootle/sam-vit-base")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("aradootle/sam-vit-base") model = AutoModelForMaskGeneration.from_pretrained("aradootle/sam-vit-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 374 Bytes
c2fbc3b | 1 2 3 4 5 6 7 8 9 10 11 12 13 | from handler import EndpointHandler
# init handler
my_handler = EndpointHandler(path=".")
# prepare sample payload
payload = {"inputs": "I am quite excited how this will turn out", "imageUrl": "https://res.cloudinary.com/dvfgdnfzd/image/upload/v1693510414/nvae1t0lvgzavfkgb45j.png"}
# test the handler
payload=my_handler(payload)
# show results
print("payload", payload) |