Run via API

To run via API, instead of duplicating the LGM-tiny space, duplicate the LGM-tiny-api space. This contains the following app.py.

import gradio as gr
from gradio_client import Client, file


def run(image_url):
    client = Client("dylanebert/LGM-tiny")
    image = file(image_url)
    result = client.predict(image, api_name="/predict")
    return result


demo = gr.Interface(
    fn=run,
    title="LGM Tiny API",
    description="An API wrapper for [LGM Tiny](https://huggingface.co/spaces/dylanebert/LGM-tiny). Intended as a resource for the [ML for 3D Course](https://huggingface.co/learn/ml-for-3d-course).",
    inputs=gr.Textbox(label="Image URL", placeholder="Enter image URL, e.g. https://huggingface.co/datasets/dylanebert/iso3d/resolve/main/jpg@512/a_cat_statue.jpg"),
    outputs=gr.Model3D(),
    examples=[
        "https://huggingface.co/datasets/dylanebert/iso3d/resolve/main/jpg@512/a_cat_statue.jpg"
    ],
    allow_duplication=True,
)
demo.queue().launch()

This will work on CPU, but relies on the original LGM-tiny, instead of your custom model. However, is your focus is on UI/UX or downstream tasks, this may be acceptable.

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