Deleted

streamlit_app.py

@@ -1,36 +0,0 @@
-import streamlit as st
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-
-# Load the Phi 2 model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained(
-    "microsoft/phi-2",
-    trust_remote_code=True
-)
-
-model = AutoModelForCausalLM.from_pretrained(
-    "microsoft/phi-2",
-    device_map="auto",
-    trust_remote_code=True
-)
-
-# Streamlit UI
-st.title("Microsoft Phi 2 Streamlit App")
-
-# User input prompt
-prompt = st.text_area("Enter your prompt:", """Write a story about Nasa""")
-
-# Generate output based on user input
-if st.button("Generate Output"):
-    with torch.no_grad():
-        token_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
-        output_ids = model.generate(
-            token_ids.to(model.device),
-            max_new_tokens=512,
-            do_sample=True,
-            temperature=0.3
-        )
-
-    output = tokenizer.decode(output_ids[0][token_ids.size(1):])
-    st.text("Generated Output:")
-    st.write(output)