Instructions to use kemalcankara/anlp2023_fall_nerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kemalcankara/anlp2023_fall_nerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kemalcankara/anlp2023_fall_nerModel")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kemalcankara/anlp2023_fall_nerModel") model = AutoModelForTokenClassification.from_pretrained("kemalcankara/anlp2023_fall_nerModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3d89e12be8ada8c5adcd193874c35c2dde102f64bb08a659f39272811897c93
- Size of remote file:
- 261 MB
- SHA256:
- a4228144da615c27dd2ad236d4dc2e291ac2889e843856a74dba2c1db22af2bf
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