Instructions to use cyc900908/Lab5_SAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cyc900908/Lab5_SAM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="cyc900908/Lab5_SAM")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("cyc900908/Lab5_SAM") model = AutoModelForMaskGeneration.from_pretrained("cyc900908/Lab5_SAM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 468 Bytes
29be7c6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"_name_or_path": "facebook/sam-vit-base",
"architectures": [
"SamModel"
],
"initializer_range": 0.02,
"mask_decoder_config": {
"model_type": ""
},
"model_type": "sam",
"prompt_encoder_config": {
"model_type": ""
},
"torch_dtype": "float32",
"transformers_version": "4.46.3",
"vision_config": {
"dropout": 0.0,
"initializer_factor": 1.0,
"intermediate_size": 6144,
"model_type": "",
"projection_dim": 512
}
}
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