# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("mask-generation", model="nasskall/vitiligo")# Load model directly
from transformers import AutoProcessor, AutoModelForMaskGeneration
processor = AutoProcessor.from_pretrained("nasskall/vitiligo")
model = AutoModelForMaskGeneration.from_pretrained("nasskall/vitiligo")Quick Links
vitiligo
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 4.42.0.dev0
- TensorFlow 2.15.0
- Tokenizers 0.19.1
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Base model
facebook/sam-vit-base
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