Instructions to use batterydata/bert-abbrev-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use batterydata/bert-abbrev-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="batterydata/bert-abbrev-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("batterydata/bert-abbrev-uncased") model = AutoModelForTokenClassification.from_pretrained("batterydata/bert-abbrev-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f375864f372425313f4d6ee97ee135e99b8aa97d2cdc81eb721f7c0276f345b
- Size of remote file:
- 3.18 kB
- SHA256:
- 74091480529cbc45edd6be879295be8fc2622d6fe9b175a2e1caf3200c88cebe
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