Update app.py

app.py

@@ -1,16 +1,16 @@
 # app.py
 
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForMaskedLM, pipeline
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 import torch
 
-# Step 1: Set up Bio_ClinicalBERT model for medical text generation
+# Step 1: Set up BioGPT model for medical text generation
 device = 0 if torch.cuda.is_available() else -1  # Set to 0 for GPU, -1 for CPU
-model_name = "emilyalsentzer/Bio_ClinicalBERT"  # Bio_ClinicalBERT model for medical context
+model_name = "microsoft/BioGPT"  # Use BioGPT model for medical context
 
 # Load tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForMaskedLM.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
 # Create a text generation pipeline with the loaded model
 chatbot = pipeline(
@@ -45,4 +45,4 @@ iface = gr.Interface(
 )
 
 # Step 4: Launch the Gradio app
-iface.launch()
+iface.launch(share=True)  # Enable sharing