Image Segmentation
Transformers
TensorBoard
Safetensors
mask2former
instance-segmentation
vision
Generated from Trainer
Instructions to use yeray142/finetune-instance-segmentation-mini-mask2former_augmentation_default_backboneFrozen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yeray142/finetune-instance-segmentation-mini-mask2former_augmentation_default_backboneFrozen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="yeray142/finetune-instance-segmentation-mini-mask2former_augmentation_default_backboneFrozen")# Load model directly from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("yeray142/finetune-instance-segmentation-mini-mask2former_augmentation_default_backboneFrozen") model = Mask2FormerForUniversalSegmentation.from_pretrained("yeray142/finetune-instance-segmentation-mini-mask2former_augmentation_default_backboneFrozen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71097bd0b4d4b2145eeaf2d4d6160538a5568bef9a0e8834e13637d778f69ae4
- Size of remote file:
- 5.43 kB
- SHA256:
- d75ff91664657d5fb48ae8c9af28d67e996b036d60a86d505457d5bd4eb787af
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