Instructions to use lee-910530/SAM-Road-Pothole-Segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lee-910530/SAM-Road-Pothole-Segmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="lee-910530/SAM-Road-Pothole-Segmentation", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("lee-910530/SAM-Road-Pothole-Segmentation") model = AutoModelForMaskGeneration.from_pretrained("lee-910530/SAM-Road-Pothole-Segmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
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"torch_dtype": "float32"
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"transformers_version": "4.
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"vision_config": {
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"attention_dropout": 0.0,
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"dropout": 0.0,
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"transformers_version": "4.51.0.dev0",
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"vision_config": {
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"attention_dropout": 0.0,
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"dropout": 0.0,
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model.safetensors
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size 374979376
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