Instructions to use Linhz/bert-base-uncased-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Linhz/bert-base-uncased-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Linhz/bert-base-uncased-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Linhz/bert-base-uncased-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("Linhz/bert-base-uncased-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 684093198325a314cc6d4aeadf6d0d0d9769323b261c1bb789d5fb06c44612e0
- Size of remote file:
- 5.11 kB
- SHA256:
- ae6bddc36860504de819aaac1178dfab8c8ecf9d689ab86a1982abf077504b5c
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