Instructions to use maydogan/multilingual-ner-model-with-code23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maydogan/multilingual-ner-model-with-code23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="maydogan/multilingual-ner-model-with-code23")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("maydogan/multilingual-ner-model-with-code23") model = AutoModelForTokenClassification.from_pretrained("maydogan/multilingual-ner-model-with-code23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11a98f9b34fbbceddb42e9e7e2ab3465cbc1eff0037a9c6b9fb0db60504f4d49
- Size of remote file:
- 5.84 kB
- SHA256:
- 01e19ee427d29281cfee65febf677fd6ffc6222a35a5442ceee9de451f2b1a3f
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