Add application file

app.py

@@ -1,17 +1,43 @@
-import streamlit as st
-
 # ran this on command line first in directory where I am putting app.py: git clone https://huggingface.co/spaces/brdemorin/chat
+# this will create a "chat" directory. This "app.py" file will need to be saved to that chat directory
+# change directory in command line to: C:\Users\brian.morin\Documents\HuggingFace\chat
+# then do the below. Must do the below everytime I make changes to app.py
+
+"""
+git add app.py
+git commit -m "Add application file"
+git push
+"""
+# I'm not sure if I actually need to do this: in your terminal, navigate to the directory containing your app.py file and run the command: streamlit run app.py
+
+# then navigate here: https://huggingface.co/spaces/brdemorin/chat
+
+
+
+
+
+
+
+
+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
 x = st.slider('Select a value')
 st.write(x, 'squared is', x * x)
 
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("brdemorin/Phi3-custom_60-steps")
+model = AutoModelForCausalLM.from_pretrained("brdemorin/Phi3-custom_60-steps")
 
-# change directory in command line to: C:\Users\brian.morin\Documents\HuggingFace
+# Create a text input for the user to enter their message
+user_input = st.text_input("Enter your message:")
 
-# then do the below to commit and push:
+# When the user enters a message and presses enter, generate a response
+if user_input:
+    # Encode the user's message and pass it to the model
+    input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
+    generated_response_ids = model.generate(input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
 
-"""
-git add app.py
-git commit -m "Add application file"
-git push
-"""
+    # Decode the model's output IDs to a string and display it
+    generated_response = tokenizer.decode(generated_response_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
+    st.write(generated_response)