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#!/usr/bin/env python
from __future__ import annotations
import gradio as gr
from model_list import ModelList
DESCRIPTION = '# Explore Biology & Biochemistry Foundation Models 🧬'
NOTES = '''
Credits to [this nice model list](https://compoundvc.notion.site/compoundvc/474885e638e94e44a1aab4d3124e3d6a?v=299bce7af785413da4c9f36837c03aaf) for some of the models listed here!
'''
FOOTER = ''''''
def main():
model_list = ModelList()
with gr.Blocks(css='style.css') as demo:
gr.Markdown(DESCRIPTION)
search_box = gr.Textbox(
label='Search Model Name',
placeholder=
'You can search for titles with regular expressions. e.g. (?<!sur)face',
max_lines=1)
case_sensitive = gr.Checkbox(label='Case Sensitive')
filter_names = gr.CheckboxGroup(choices=[
'Paper',
'Code',
'Model Weights',
], label='Filter')
data_type_names = [
'DNA', 'scRNA', 'scRNA perturbation', 'protein language model', 'protein structure prediction',
'protein generation', 'protein function prediction', 'antibody structure prediction', 'antibody language model', 'molecules',
'ligand generation', 'reaction-to-enzyme', 'enzyme generation', 'epigenetics',
]
data_types = gr.CheckboxGroup(choices=data_type_names,
value=data_type_names,
label='Type')
# model_type_names = [
# 'GPT2', 'GPT-Neo', 'GPT-NeoX', 'ESM', 'BERT', 'RoBERTa', 'BART', 'T5', 'MPNN', 'diffusion', 'custom model'
# ]
# model_types = gr.CheckboxGroup(choices=model_type_names,
# value=model_type_names,
# label='Base Model')
search_button = gr.Button('Search')
number_of_models = gr.Textbox(label='Number of Models Found')
table = gr.HTML(show_label=False)
gr.Markdown(NOTES)
gr.Markdown(FOOTER)
demo.load(fn=model_list.render,
inputs=[
search_box,
case_sensitive,
filter_names,
data_types,
#model_types
],
outputs=[
number_of_models,
table,
])
search_box.submit(fn=model_list.render,
inputs=[
search_box,
case_sensitive,
filter_names,
data_types,
#model_types
],
outputs=[
number_of_models,
table,
])
search_button.click(fn=model_list.render,
inputs=[
search_box,
case_sensitive,
filter_names,
data_types,
#model_types
],
outputs=[
number_of_models,
table,
])
demo.launch(enable_queue=True, share=False)
if __name__ == '__main__':
main()
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