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:
- 4f6b563881e1b53b91ac96cee0b352af226e0c0d00c371c908e65abe0a040574
- Size of remote file:
- 431 MB
- SHA256:
- 8eb926daceb1e3762fb69c6b97031018ca49acbaa6f5e3dd6baa946d4d96525b
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