Instructions to use amrithanandini/bert-relay-decoding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amrithanandini/bert-relay-decoding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="amrithanandini/bert-relay-decoding")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("amrithanandini/bert-relay-decoding") model = AutoModelForTokenClassification.from_pretrained("amrithanandini/bert-relay-decoding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 753ef0d03abdf7b4095e4d5ce14984d5a52b01b657f8f161d3d9aac59741aad2
- Size of remote file:
- 5.05 kB
- SHA256:
- f871c486c3b94d81505fa38679123f361c01c8ff263dc7813358af5377cfba58
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