Create app.py

app.py

@@ -0,0 +1,25 @@
+import streamlit as st
+from transformers import AutoModelWithLMHead, AutoTokenizer
+
+# Title of the page
+st.title("Text Generation with Huggingface Model")
+
+# Tokenizer model selection
+model_name = st.selectbox("Select a Huggingface model",
+                         ["distilbert-base-cased",
+                          "gpt2",
+                          "xlm-roberta-base"])
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelWithLMHead.from_pretrained(model_name)
+
+# Text box where the user can enter the text
+text = st.text_area("Enter the text",
+                    "Type your text here...")
+
+# Generate the text
+if st.button("Generate"):
+    input_ids = tokenizer.encode(text, return_tensors="pt")
+    output_ids = model.generate(input_ids)[0]
+    generated_text = tokenizer.decode(output_ids)
+    st.write(generated_text)