Instructions to use deprem-ml/deprem-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deprem-ml/deprem-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="deprem-ml/deprem-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("deprem-ml/deprem-ner") model = AutoModelForTokenClassification.from_pretrained("deprem-ml/deprem-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 248574f2acd865e06c8c138f68c910bb9f92d087db4c2a623b241bccdd1dfa7a
- Size of remote file:
- 440 MB
- SHA256:
- bf391d9593e46a28c72c354fddec4bf0c32ff3b82d906b7e304ac5434e56ee76
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