Instructions to use tiny-random/sam3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiny-random/sam3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="tiny-random/sam3")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("tiny-random/sam3") model = AutoModel.from_pretrained("tiny-random/sam3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56ad8d663ce1572505eefa6a2fa431830def937f47e438a553de2d2172dfa4d4
- Size of remote file:
- 3.81 MB
- SHA256:
- 39846bd3215ea587e1858ec5be2ee0b47cc7af99d941237ad52165abbfa8d18c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.