Instructions to use danelcsb/sam2_hiera_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danelcsb/sam2_hiera_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="danelcsb/sam2_hiera_small")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("danelcsb/sam2_hiera_small") model = AutoModel.from_pretrained("danelcsb/sam2_hiera_small") - Notebooks
- Google Colab
- Kaggle
File size: 678 Bytes
2f17fe9 | 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 35 36 37 | {
"crop_size": null,
"data_format": "channels_first",
"default_to_square": true,
"device": null,
"disable_grouping": null,
"do_center_crop": null,
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "Sam2ImageProcessorFast",
"image_std": [
0.229,
0.224,
0.225
],
"input_data_format": null,
"mask_size": {
"height": 256,
"width": 256
},
"processor_class": "Sam2Processor",
"resample": 2,
"rescale_factor": 0.00392156862745098,
"return_tensors": null,
"size": {
"height": 1024,
"width": 1024
}
}
|