Instructions to use jtlicardo/bert-finetuned-bpmn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jtlicardo/bert-finetuned-bpmn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jtlicardo/bert-finetuned-bpmn")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jtlicardo/bert-finetuned-bpmn") model = AutoModelForTokenClassification.from_pretrained("jtlicardo/bert-finetuned-bpmn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c1ef4b870554db46aa011e2bbb0856aa279e142027b2116ea3260db23bb4d05
- Size of remote file:
- 3.39 kB
- SHA256:
- 14a3f6b87583087f67326415388d16c19d765173173b5dfbbd1157da94a24760
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