app created

app.py

@@ -0,0 +1,16 @@
+import streamlit as st
+from transformers import (GPT2Tokenizer, GPT2ForSequenceClassification)
+
+model = GPT2ForSequenceClassification.from_pretrained(pretrained_model_name_or_path='ErnestBeckham/gpt-2-finetuned-ai-content')
+tokenizer = GPT2Tokenizer.from_pretrained(pretrained_model_name_or_path='ErnestBeckham/gpt2-tokenizer-ai-content')
+
+text = st.text_area("Paste your Content")
+
+if text:
+    tokenized_input = tokenizer(sentence, return_tensors='pt')
+    with torch.no_grad():
+    outputs = model(**tokenized_input)
+
+    logits = outputs.logits
+    predicted_class = torch.argmax(logits, dim=-1).item()
+    st.json(predicted_class)