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import gradio as gr |
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import torch |
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from huggingface_hub import hf_hub_download |
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def load_model_from_hub(repo_id, filename): |
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model_path = hf_hub_download(repo_id=repo_id, filename=filename) |
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model = torch.load(model_path, weights_only=False, map_location='cpu') |
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model.eval() |
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return model |
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def predict(text, model): |
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with torch.no_grad(): |
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output = model(text) |
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return float(output) |
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def create_gradio_app(): |
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repo_id = "jane-street/2025-03-10" |
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model_filename = "model.pt" |
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model = load_model_from_hub(repo_id, model_filename) |
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with gr.Blocks() as demo: |
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gr.Markdown(''' |
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Today I went on a hike and found a pile of tensors hidden underneath a neolithic burial mound! |
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I sent it over to the local neural plumber, and they managed to cobble together this. |
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**[model.pt](https://huggingface.co/jane-street/2025-03-10/tree/main)** |
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Anyway, I'm not sure what it does yet, but it must have been important to this past civilization. |
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Maybe start by looking at the last two layers. |
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''') |
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input_text = gr.Textbox(label="Model Input", value='vegetable dog') |
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output = gr.Number(label="Model Output") |
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input_text.submit(fn=lambda x: predict(x, model), inputs=input_text, outputs=output) |
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gr.Markdown(''' |
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If you do figure it out, please let us know at *archaeology@janestreet.com*. |
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--- |
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Solved by |
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- Noa Nabeshima and Collin Gray |
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- Andrew Peterson |
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- Alex Waese-Perlman |
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- David Rapisarda and Jayant Khatkar |
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- Ryan Bruntz |
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- Sam Corbett |
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- Can Elbirlik |
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- Benedict Davies |
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- Вадим Калашников |
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- Géza Herman |
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- Jack Murphy |
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- Snehal Verma |
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- Sean Osier |
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- Sam Patterson |
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- Nikita Klyuchnikov |
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- Xiao Zheng |
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- Fedor Korotkiy |
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- Nick Griffiths |
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- Ujas Shah |
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- Oleh Feilo |
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- Павел Дергунов |
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- Gregor Kikelj |
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- Adir Kobovich |
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--- |
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*Learn more at [janestreet.com](https://jane-st.co/3YfP5WK)*. |
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''') |
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demo.queue(max_size=1_000) |
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return demo |
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if __name__ == "__main__": |
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app = create_gradio_app() |
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app.launch(show_api=False) |
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