Instructions to use sarveshsk/bert_base_uncase_Conll2012 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sarveshsk/bert_base_uncase_Conll2012 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sarveshsk/bert_base_uncase_Conll2012")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sarveshsk/bert_base_uncase_Conll2012") model = AutoModelForTokenClassification.from_pretrained("sarveshsk/bert_base_uncase_Conll2012") - Notebooks
- Google Colab
- Kaggle
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README.md
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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from transformers import pipeline
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tokenizer = AutoTokenizer.from_pretrained("
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model = AutoModelForTokenClassification.from_pretrained("
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nlp = pipeline("ner", model=model, tokenizer=tokenizer)
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example = "Plan a trip from W Broad Street Columbus to Hazel Street Louisville Kentucky USA on Sunday at 5 o Clock"
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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from transformers import pipeline
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tokenizer = AutoTokenizer.from_pretrained("sarveshsk/bert_base_uncase_Conll2012")
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model = AutoModelForTokenClassification.from_pretrained("sarveshsk/bert_base_uncase_Conll2012")
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nlp = pipeline("ner", model=model, tokenizer=tokenizer)
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example = "Plan a trip from W Broad Street Columbus to Hazel Street Louisville Kentucky USA on Sunday at 5 o Clock"
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