Mask Generation
Transformers
Safetensors
English
sam3
feature-extraction
unsloth
sam3.1
segment-anything
segmentation
text-prompted-segmentation
inpainting
bf16
fp8
int8
Instructions to use unsloth/sam3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/sam3.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="unsloth/sam3.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("unsloth/sam3.1") model = AutoModel.from_pretrained("unsloth/sam3.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
File size: 613 Bytes
6cfffd0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"image_processor": {
"data_format": "channels_first",
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "Sam3ImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"mask_size": {
"height": 288,
"width": 288
},
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 1008,
"width": 1008
}
},
"point_pad_value": -10,
"processor_class": "Sam3Processor",
"target_size": 1008
}
|