Instructions to use yonigozlan/EdgeTAM-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yonigozlan/EdgeTAM-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="yonigozlan/EdgeTAM-hf")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("yonigozlan/EdgeTAM-hf") model = AutoModel.from_pretrained("yonigozlan/EdgeTAM-hf") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f58b6d5093c72392b413fb78a02cf7dc778ea7186a9e367ba0ac90f3b03c3a68
- Size of remote file:
- 55.9 MB
- SHA256:
- 8858f8e4757b0b96dab8763f296ecffd845efbbbf698f64163cfa20a63d5fff4
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