Instructions to use deprem-ml/adres_ner_v12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deprem-ml/adres_ner_v12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="deprem-ml/adres_ner_v12")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("deprem-ml/adres_ner_v12") model = AutoModelForTokenClassification.from_pretrained("deprem-ml/adres_ner_v12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ce653dcbea497bcd94f35897a564ba8906f1765d5a56e948e0c86b9f776b81f
- Size of remote file:
- 3.45 kB
- SHA256:
- 9bde9906e8c57d067cb891c129c695a7aa016cb0938033694d1f7d6fcee72766
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