# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("hadiaskari98/Software_NER_prod")
model = AutoModelForTokenClassification.from_pretrained("hadiaskari98/Software_NER_prod")Quick Links
How to use
tokenizer = AutoTokenizer.from_pretrained("hadiaskari98/Software_NER_prod")
model = AutoModelForTokenClassification.from_pretrained("hadiaskari98/Software_NER_prod")
nlp = pipeline("ner", model=model, tokenizer=tokenizer)
example = "Windows XP is an example of an operating system."
ner_results = nlp(example)
print(ner_results)
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Model tree for hadiaskari98/Software_NER_prod
Base model
google-bert/bert-large-cased
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hadiaskari98/Software_NER_prod")