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Update app.py
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app.py
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@@ -1,3 +1,13 @@
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import os
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import gradio as gr
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@@ -84,6 +94,8 @@ def sample_at_length(l:int, seed:int):
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interface = gr.Interface(
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fn=sample_at_length,
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inputs=[
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gr.Number(value=80, label="Protein backbone length to generate", show_label=True, precision=0),
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gr.Number(value=42, label="Random seed", show_label=True, precision=0),
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"""
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foldingdiff implements a diffusion model for generating protein structures. Inspired by the biological folding process,
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we perform diffusion on the angles between amino acid residues rather than the absolute 3D coordinates of each residue.
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By effectively treating each residue as its own reference frame, we shift the equivariance constraints into the
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representation space itself; this allows us to use a vanilla transformer model as our model. Here, we provide a simple
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online interface for generating single backbones with a given length, starting from a given random seed.
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See our preprint at https://arxiv.org/abs/2209.15611 and our full codebase at https://github.com/microsoft/foldingdiff
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"""
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import os
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import gradio as gr
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interface = gr.Interface(
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fn=sample_at_length,
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title="foldingdiff - protein backbone structure generation with diffusion models",
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description=__doc__,
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inputs=[
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gr.Number(value=80, label="Protein backbone length to generate", show_label=True, precision=0),
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gr.Number(value=42, label="Random seed", show_label=True, precision=0),
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