example using model with huggingface pipeline

pipeline_example.py

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+"""Example of inference with these models using a huggingface pipeline."""
+
+from transformers import pipeline
+
+# Available models
+# lrei/roberta-large-emolit
+# lrei/roberta-base-emolit
+# lrei/distilroberta-base-emolit
+MODEL = "lrei/roberta-large-emolit"
+
+
+classifier = pipeline(
+    "text-classification",
+    model=MODEL,
+    device=None,
+)
+
+texts = ["This is so much fun!",
+         "I want to go back home to my dogs, i'll be happy to go back to them."]
+
+
+print()
+results = classifier(texts, top_k=None, function_to_apply="sigmoid")
+for t, r in zip(texts, results):
+    print(t)
+    print(r)
+    print("\n")