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
Download processor_config.json from unsloth/sam3.1: direct link, hf CLI and curl.
- Browser
- Download file 613 Bytes
-
https://huggingface.co/unsloth/sam3.1/resolve/main/processor_config.json
- Command line
-
hf download hf://unsloth/sam3.1/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/unsloth/sam3.1/resolve/main/processor_config.json
613 Bytes
| { | |
| "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 | |
| } | |