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:
- b81fab13db65bd1db8d94393d1c0bfdb8dcdd08c1294b499434ae34dbcd51cd2
- Size of remote file:
- 862 MB
- SHA256:
- 141e1fa5811bd084e7da2c9f04165a46a7869884608c3d471dc29cee85f06220
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