Instructions to use EddyGiusepe/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EddyGiusepe/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EddyGiusepe/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EddyGiusepe/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("EddyGiusepe/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 545911762299cdc49a22f01ab388d2f9550358f2fd8a708f0e921c620307b265
- Size of remote file:
- 3.38 kB
- SHA256:
- 472d52944a89570a9aaaf8052cfacd2e271b05f0b46ba6d7bd3911a81b71ce00
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