Instructions to use ashaduzzaman/sam-finetuned-breast-cancer-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashaduzzaman/sam-finetuned-breast-cancer-segmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="ashaduzzaman/sam-finetuned-breast-cancer-segmentation")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("ashaduzzaman/sam-finetuned-breast-cancer-segmentation") model = AutoModelForMaskGeneration.from_pretrained("ashaduzzaman/sam-finetuned-breast-cancer-segmentation") - Notebooks
- Google Colab
- Kaggle
sam-finetuned-breast-cancer-segmentation
This model is a fine-tuned version of facebook/sam-vit-base on an unknown dataset. It achieves the following results on the evaluation set:
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.44.0.dev0
- TensorFlow 2.15.0
- Tokenizers 0.19.1
- Downloads last month
- 12
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Model tree for ashaduzzaman/sam-finetuned-breast-cancer-segmentation
Base model
facebook/sam-vit-base