Instructions to use MiBo/SegBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MiBo/SegBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MiBo/SegBert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MiBo/SegBert") model = AutoModelForTokenClassification.from_pretrained("MiBo/SegBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eabdc20b188fd8ef1e9affe1e8a59f0233840d634ab47e269449174687a36439
- Size of remote file:
- 440 MB
- SHA256:
- 16df9aa5eb72b459904841a3b6832476e5650238a51ba643a8b1a483355bc221
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