Finance_NLP_Toolkit / inference_examples.py
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Create inference_examples.py
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from transformers import pipeline, AutoTokenizer, AutoModelForTokenClassification
def demo_sentiment():
clf = pipeline("sentiment-analysis", model="YOUR-USERNAME/Finance-NLP-Toolkit")
print(clf("Shares plunged after the weak revenue outlook."))
def demo_ner():
tok = AutoTokenizer.from_pretrained("YOUR-USERNAME/Finance-NLP-Toolkit", revision="ner")
ner_model = AutoModelForTokenClassification.from_pretrained("YOUR-USERNAME/Finance-NLP-Toolkit", revision="ner")
ner = pipeline("token-classification", model=ner_model, tokenizer=tok, aggregation_strategy="simple")
print(ner("Microsoft will acquire Nuance for $19.7 billion in 2025."))
if __name__ == "__main__":
demo_sentiment()
demo_ner()