Image Segmentation
Transformers
Safetensors
sam2
mask-generation
vision
sam
trackio
Generated from Trainer
Instructions to use merve/sam2-large-micromat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use merve/sam2-large-micromat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="merve/sam2-large-micromat")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("merve/sam2-large-micromat") model = AutoModelForMaskGeneration.from_pretrained("merve/sam2-large-micromat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from merve/sam2-large-micromat: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/merve/sam2-large-micromat/resolve/main/training_args.bin
- Command line
-
hf download hf://merve/sam2-large-micromat/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/merve/sam2-large-micromat/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- 6b5c78c1a9db151031b9c0982575c246f2d50089fcc93a9df0e161d4dfc379fe
- Size of remote file:
- 5.33 kB
- SHA256:
- 78ee15267263f02b3d1d1a6bee28739db0b539013a2e1854f281101109583bd5
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