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:
- e9b26b9f7988c02d430aa9bae904b94611f01d4fa2769c5137a6a61e3cc30d48
- Size of remote file:
- 441 MB
- SHA256:
- cddb2909694b24bdbb5ca3854bc33638dde7f3f2597373aebc44e6c42a96e2a0
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