Instructions to use THemidli/applied-ner-stage4-bert-mini-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use THemidli/applied-ner-stage4-bert-mini-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="THemidli/applied-ner-stage4-bert-mini-final")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("THemidli/applied-ner-stage4-bert-mini-final") model = AutoModelForTokenClassification.from_pretrained("THemidli/applied-ner-stage4-bert-mini-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66821c805cd09f979b720703480a8ce22ff4b9ebf7e5ed643e65b28b9c53d017
- Size of remote file:
- 5.27 kB
- SHA256:
- 0700c2286e212238aad06a343f5c246ac3cac639535d11109c3df41485f94372
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