added Phi-3.5-mini-instruct

app.py

@@ -2,11 +2,13 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-1_5")
-model = AutoModelForCausalLM.from_pretrained(
-    "microsoft/phi-1_5",
-    device_map="auto"
-)
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3.5-mini-instruct", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3.5-mini-instruct",
+    device_map="auto",
+    trust_remote_code=True)
 
 # Function to generate text based on the prompt
 def generate_text(prompt, max_length=100):
@@ -20,6 +22,6 @@ iface = gr.Interface(
     fn=generate_text,
     inputs="text",
     outputs="text",
-    title="Microsoft Phi 1.5B Text Generation"
+    title="Microsoft Phi 3.5B Instruct - Text Generation"
 )
 iface.launch()