compare

app.py

@@ -4,31 +4,27 @@ import torch
 import numpy as np
 from transformers import pipeline
 
-examples = [['Q: Can Geoffrey Hinton have a conversation with George Washington? Give the rationale before answering.'],['Translate to German:  My name is Arthur'], ['Please answer the following question. What is the boiling point of Nitrogen?']] 
+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']] 
 
 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-Large", device="cuda:0", model_kwargs={"torch_dtype":torch.bfloat16})
-pipe_flan_t5 = pipeline("text-generation", model="google/flan-t5-xxl", device="cuda:0", model_kwargs={"torch_dtype":torch.bfloat16})
-#pipe_gpt2 = pipeline("text-generation", model="gpt2", device="cuda:0", model_kwargs={"torch_dtype":torch.bfloat16})
-#pipe_flan_ul2 = pipeline("text-generation", model="google/flan-ul2", device="cuda:0", model_kwargs={"torch_dtype":torch.bfloat16})
+pipe_biogpt = pipeline("text-generation", model="microsoft/BioGPT-Large", device="cuda:0", model_kwargs={"torch_dtype":torch.bfloat16})
+pipe_biomedlm = pipeline("text-generation", model="stanford-crfm/BioMedLM", device="cuda:0", model_kwargs={"torch_dtype":torch.bfloat16})
 pipe_galactica = pipeline("text-generation", model="facebook/galactica-1.3b", device="cuda:0", model_kwargs={"torch_dtype":torch.bfloat16})
 
-title = "LLM vs LLM"
-description = "**Disclaimer:** this demo was made for research purposes."
+title = "Compare generative biomedical LLMs!"
+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_flan_t5 = pipe_flan_t5(text, max_length=100)[0]["generated_text"]
-  #output_gpt2 = pipe_gpt2(text, max_length=100)[0]["generated_text"]
-  #pipe_flan_ul2 = pipe_flan_t5(text, max_length=100)[0]["generated_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_flan_t5,
-      #output_gpt2,
-      #pipe_flan_ul2,
+      output_biogpt, 
+      output_biomedlm,
       output_galactica
   ]
 
@@ -36,11 +32,9 @@ io = gr.Interface(
   inference,
   gr.Textbox(lines=3),
   outputs=[
-    #gr.Textbox(lines=3, label="Microsoft: BioGPT-Large"),
-    gr.Textbox(lines=3, label="Google: FLAN-T5-XXL"),
-    #gr.Textbox(lines=3, label="GPT-2"),
-    #gr.Textbox(lines=3, label="Google: FLAN-UL2"),
-    gr.Textbox(lines=3, label="Facebook: Galactica 1.3B"),
+    gr.Textbox(lines=3, label="BioGPT-Large"),
+    gr.Textbox(lines=3, label="BioMedLM (fka PubmedGPT)"),
+    gr.Textbox(lines=3, label="Galactica 1.3B"),
   ],
   title=title,
   description=description,