Instructions to use Justin331/sam3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Justin331/sam3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="Justin331/sam3")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Justin331/sam3") model = AutoModel.from_pretrained("Justin331/sam3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| numpy | |
| torch | |
| torchvision | |
| Pillow | |
| scipy | |
| pycocotools | |
| matplotlib | |
| scikit-learn | |
| scikit-image | |
| tqdm | |
| huggingface-hub | |
| omegaconf | |
| hydra-core | |
| submitit | |
| decord | |
| psutil | |
| triton | |
| ftfy | |
| regex | |
| einops | |
| torchmetrics | |
| pandas | |
| openai | |
| typing-extensions | |
| opencv-python-headless | |
| iopath | |
| timm | |
| . | |