Instructions to use arnolfokam/bert-base-uncased-pcm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arnolfokam/bert-base-uncased-pcm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arnolfokam/bert-base-uncased-pcm")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arnolfokam/bert-base-uncased-pcm") model = AutoModelForTokenClassification.from_pretrained("arnolfokam/bert-base-uncased-pcm") - Notebooks
- Google Colab
- Kaggle
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Parent(s): a717809
Update README.md
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README.md
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@@ -66,7 +66,7 @@ tokenizer = AutoTokenizer.from_pretrained("arnolfokam/bert-base-uncased-pcm")
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model = AutoModelForTokenClassification.from_pretrained("bert-base-uncased-pcm")
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nlp = pipeline("ner", model=model, tokenizer=tokenizer)
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example = "
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ner_results = nlp(example)
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print(ner_results)
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model = AutoModelForTokenClassification.from_pretrained("bert-base-uncased-pcm")
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nlp = pipeline("ner", model=model, tokenizer=tokenizer)
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example = "Mixed Martial Arts joinbodi, Ultimate Fighting Championship, UFC don decide say dem go enta back di octagon on Saturday, 9 May, for Jacksonville, Florida."
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ner_results = nlp(example)
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print(ner_results)
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