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:
- 3d302761e55fd04d449ae255476b87aa3b5b42892fe5ee9fc54e6211740a0381
- Size of remote file:
- 440 MB
- SHA256:
- f761a4b7efb531aa990c4cae3dbe4d487dacf815dd54f80d5277fc05ed65ff53
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