katielink commited on
Commit
b40d807
1 Parent(s): c4f4d6f

Update app.py

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Files changed (1) hide show
  1. app.py +4 -32
app.py CHANGED
@@ -8,12 +8,12 @@ name_list = ['microsoft/biogpt', 'stanford-crfm/BioMedLM']
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  examples = [['COVID-19 is'],['A 65-year-old female patient with a past medical history of']]
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- #import torch
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- #print(f"Is CUDA available: {torch.cuda.is_available()}")
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- #print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
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  pipe_biogpt = pipeline("text-generation", model="microsoft/biogpt")
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- pipe_biomedlm = pipeline("text-generation", model="stanford-crfm/BioMedLM")
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  title = "Compare generative biomedical LLMs!"
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  description = "This demo compares [BioGPT](https://huggingface.co/microsoft/biogpt) and [BioMedLM](https://huggingface.co/stanford-crfm/BioMedLM)."
@@ -38,31 +38,3 @@ io = gr.Interface(
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  examples=examples
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  )
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  io.launch()
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-
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- """
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- def generate_biomedical(text):
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- interfaces = [gr.Interface.load(name) for name in name_list]
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- return [interface(text) for interface in interfaces]
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-
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- def set_example(example: list) -> dict:
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- return gr.Textbox.update(value=example[0])
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-
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- with gr.Blocks() as demo:
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- gr.Markdown("# Compare generative biomedical LLMs")
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- with gr.Box():
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- with gr.Row():
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- with gr.Column():
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- input_text = gr.Textbox(label = "Write your text here", lines=4)
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- with gr.Row():
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- btn = gr.Button("Generate ✨")
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-
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- example_text = gr.Dataset(components=[input_text], samples=examples)
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- example_text.click(fn=set_example,
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- inputs = example_text,
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- outputs= example_text.components)
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- with gr.Column():
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- gr.Markdown("Let’s compare!")
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- btn.click(generate_biomedical, inputs = input_text, outputs = [gr.Textbox(label=name_list[_], lines=4) for _ in range(len(name_list))])
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-
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- demo.launch(enable_queue=True, debug=True)
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- """
 
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  examples = [['COVID-19 is'],['A 65-year-old female patient with a past medical history of']]
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+ import torch
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+ print(f"Is CUDA available: {torch.cuda.is_available()}")
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+ print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
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  pipe_biogpt = pipeline("text-generation", model="microsoft/biogpt")
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+ pipe_biomedlm = pipeline("text-generation", model="stanford-crfm/BioMedLM", device="cuda:0")
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  title = "Compare generative biomedical LLMs!"
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  description = "This demo compares [BioGPT](https://huggingface.co/microsoft/biogpt) and [BioMedLM](https://huggingface.co/stanford-crfm/BioMedLM)."
 
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  examples=examples
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  )
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  io.launch()