Create inference_examples.py

inference_examples.py

@@ -0,0 +1,15 @@
+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()