Instructions to use abhicake/fine_bg_removal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abhicake/fine_bg_removal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="abhicake/fine_bg_removal", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("abhicake/fine_bg_removal", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- baeffcd013076c14ab9de409884c40cae065f344d19687708c30d21ab3413af5
- Size of remote file:
- 134 Bytes
- SHA256:
- aaa8141adbc209cb12aa69347179a72eef72736b6729ea9a726fd5a8577d53a7
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