Instructions to use NahedAbdelgaber/updated_ner_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NahedAbdelgaber/updated_ner_base_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="NahedAbdelgaber/updated_ner_base_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("NahedAbdelgaber/updated_ner_base_model") model = AutoModelForTokenClassification.from_pretrained("NahedAbdelgaber/updated_ner_base_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee5c62c9fce7a1ede348f63ddd1e789028da8207478d493c5685bdee7cf3046b
- Size of remote file:
- 3.06 kB
- SHA256:
- a686e4fd8964aa986ff6c96a5b5e540f8555b5d9e0476b1ecc52d54b33a217e3
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