Create legacy_ver.py

This is the old code I used for the app.

legacy_ver.py

@@ -0,0 +1,26 @@
+# here are some examples for sadness, joy, anger, and optimism.
+import gradio as gr
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("barbieheimer/MND_TweetEvalBert_model")
+model = AutoModelForSequenceClassification.from_pretrained("barbieheimer/MND_TweetEvalBert_model")
+
+# We can now use the model in the pipeline.
+classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
+
+def predict(prompt):
+    completion = classifier(prompt)
+    return completion[0]["label"], completion[0]["score"]
+
+examples = [
+    ["The movie was a bummer."],
+    ["I cannot wait to watch all these movies!"],
+    ["The ending of the movie really irks me, gives me the ick fr."],
+    ["The protagonist seems to have a lot of hope...."]
+]
+
+gr.Interface.load("models/barbieheimer/MND_TweetEvalBert_model", fn=predict, title="Sentiment Analysis", examples=examples,
+    inputs=gr.inputs.Textbox(lines=5, label="Paste an Article here."),
+    outputs=[gr.outputs.Textbox(label="Label"),gr.outputs.Textbox(label="Score")],).launch()