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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7e7cfe6da38a88fa599293ec8d9379a1308c72bcdca3d7abb1822afe6b818d3
- Size of remote file:
- 1.11 GB
- SHA256:
- 3d89ae5a1a590a616f57c0ff954779a966f0dc4d11289db56a6e9cbf8adeebb7
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