Update app.py

app.py

@@ -4,26 +4,28 @@ import torch
 import numpy as np
 from transformers import pipeline
 
-name_list = ['microsoft/biogpt', 'stanford-crfm/BioMedLM']
+name_list = ['microsoft/biogpt', 'stanford-crfm/BioMedLM', 'facebook/galactica-1.3b']
 
 examples = [['COVID-19 is'],['A 65-year-old female patient with a past medical history of']] 
 
-import torch
 print(f"Is CUDA available: {torch.cuda.is_available()}")
 print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
 
 pipe_biogpt = pipeline("text-generation", model="microsoft/biogpt")
 pipe_biomedlm = pipeline("text-generation", model="stanford-crfm/BioMedLM", device="cuda:0")
+pipe_galactica = pipeline("text-generation", model="facebook/galactica-1.3b", device="cuda:0")
 
 title = "Compare generative biomedical LLMs!"
-description = "This demo compares [BioGPT](https://huggingface.co/microsoft/biogpt) and [BioMedLM](https://huggingface.co/stanford-crfm/BioMedLM). **Disclaimer:** this demo was made for research purposes only and should not be used for medical purposes."
+description = "**Disclaimer:** this demo was made for research purposes only and should not be used for medical purposes."
 
 def inference(text):
   output_biogpt = pipe_biogpt(text, max_length=100)[0]["generated_text"]
   output_biomedlm = pipe_biomedlm(text, max_length=100)[0]["generated_text"]
+  output_galactica = pipe_galactica(text, max_length=100)[0]["generated_text"]
   return [
       output_biogpt, 
-      output_biomedlm
+      output_biomedlm,
+      output_galactica
   ]
 
 io = gr.Interface(
@@ -31,7 +33,8 @@ io = gr.Interface(
   gr.Textbox(lines=3),
   outputs=[
     gr.Textbox(lines=3, label="BioGPT"),
-    gr.Textbox(lines=3, label="BioMedLM")
+    gr.Textbox(lines=3, label="BioMedLM (fka PubmedGPT)")
+    gr.Textbox(lines=3, label="Galactica")
   ],
   title=title,
   description=description,