Update app.py

app.py

@@ -1,11 +1,9 @@
-import gradio as gr
+import streamlit as st
+from transformers import pipeline
 
-title = "facebook_OPT_350m_Language_model"
-description = "Gradio Demo for facebook_OPT_350m_Language_model , OPT was predominantly pretrained with English text, but a small amount of non-English data is still present within the training corpus via CommonCrawl. The model was pretrained using a causal language modeling (CLM) objective. OPT belongs to the same family of decoder-only models like GPT-3. As such, it was pretrained using the self-supervised causal language modedling objective. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2205.01068' target='_blank'>OPT: Open Pre-trained Transformer Language Models</a></p>"
-examples = [
-    ['life is like'],
-    ["president of america is"],
-    ["  taj mahal is "]
-]
-gr.Interface.load("huggingface/facebook/opt-125m", inputs=gr.inputs.Textbox(lines=5, label="Input Text"),title=title,description=description,article=article, examples=examples,enable_queue=True).launch()
+generator = pipeline('text-generation', model="facebook/opt-125m")
+prompt = st.text_area('Enter text below to generate new text using facebook_OPT_350m_Language_model')
+
+if prompt:
+  out = generator(prompt)
+  st.json(out)