--- title: "LGM-Mini" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/d1348a8b-2e21-425e-88dd-d182a1ce8b68" updated: "2026-11-12" --- # LGM-Mini > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs a small Gradio demo built on the LGM model and several multi-view diffusion models, on a Hugging Face GPU. It suits people interested in 3D generation research who want to try or read the code. LGM-Mini is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by dylanebert ## About ### What it is LGM-Mini is a Gradio demo that names four models, ashawkey/LGM, dylanebert/LGM, dylanebert/imagedream and dylanebert/multi-view-diffusion, and one dataset called iso3d. The Space has no description of its own. Going by those names, it works on 3D content made from pictures. It runs on Hugging Face's zero-a10g GPU setting and the repository holds five files. ### Who it suits It suits people who follow 3D generation research and want to try the demo, and developers who want to read a short app that wires several models together. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | AI research | Researchers and students | Try a multi-view model demo without installing it | A student opens the Space and runs the demo. | | Graphics | 3D artists | See what a model can make from a picture | An artist tries the demo with a picture of a single object. | | Software | Developers | Read how a short app uses several models | A developer opens app.py to see which models it loads. | If you need a documented tool with known outputs, skip it, because the Space gives no description of what it returns. ### Where to use it - A web browser, through the Space's page on Hugging Face - A local copy on Windows, macOS or Linux, using Python and a capable GPU | Use case | Who | What they get back | | --- | --- | --- | | Try the demo online | Anyone | The Gradio page, running on Hugging Face's GPU | | Run it locally | Developers | The same app on your own computer, if it can run these models | | Read the code | Learners | A short app.py that loads the named models | ### How to set it up - Python and pip on Windows, macOS or Linux - The packages listed in requirements.txt - A GPU, since the hosted Space uses zero-a10g hardware 1. Install the huggingface\_hub package. 2. Download the Space into a local folder named LGM-mini. 3. Move into that folder. 4. Install gradio at version 5.49.1. 5. Install the packages listed in requirements.txt. 6. Start the app. ```sh pip install -U huggingface_hub hf download dylanebert/LGM-mini --repo-type space --local-dir LGM-mini cd LGM-mini pip install gradio==5.49.1 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space's page, or start the app locally with the command below. Then use the Gradio page that opens. ```sh python app.py ``` | Tool | What it does | | --- | --- | | app.py | The main file, which starts the Gradio app | | requirements.txt | Lists the Python packages the app needs | ### Example You run the download commands and then python app.py. The Gradio page opens in your browser, and you use it with a picture of your choice. ### For newcomers and experts If you are new, open the Space's page and try it with one simple picture. Expect to read the page itself to learn what the controls do. If you know the field, the model list mixes LGM with ImageDream and a multi-view diffusion model, which fits a pipeline from a picture to several views and then to 3D. That is a reading of the names, not a statement in the source. Open the Space or run app.py → Give the page an input → The named models run on a GPU → The page shows the result ### Good to know - The Space has no description, so what it returns is not documented - The hosted version uses a GPU, so a local run needs capable hardware - License: mit - Cost to run: none named - Data it reaches: the inputs you give the page, and the model files it names ## README ````markdown # LGM-Mini Runs a small Gradio demo built on the LGM model and several multi-view diffusion models, on a Hugging Face GPU. It suits people interested in 3D generation research who want to try or read the code. Made by dylanebert on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: LGM-Mini is a Gradio demo that names four models, ashawkey/LGM, dylanebert/LGM, dylanebert/imagedream and dylanebert/multi-view-diffusion, and one dataset called iso3d. The Space has no description of its own. Going by those names, it works on 3D content made from pictures. It runs on Hugging Face's zero-a10g GPU setting and the repository holds five files. Who it suits: It suits people who follow 3D generation research and want to try the demo, and developers who want to read a short app that wires several models together. ```table Industry | Who uses it | How they use it | Example AI research | Researchers and students | Try a multi-view model demo without installing it | A student opens the Space and runs the demo. Graphics | 3D artists | See what a model can make from a picture | An artist tries the demo with a picture of a single object. Software | Developers | Read how a short app uses several models | A developer opens app.py to see which models it loads. ``` If you need a documented tool with known outputs, skip it, because the Space gives no description of what it returns. Where to use it: - A web browser, through the Space's page on Hugging Face - A local copy on Windows, macOS or Linux, using Python and a capable GPU ```table Use case | Who | What they get back Try the demo online | Anyone | The Gradio page, running on Hugging Face's GPU Run it locally | Developers | The same app on your own computer, if it can run these models Read the code | Learners | A short app.py that loads the named models ``` How to set it up: - Python and pip on Windows, macOS or Linux - The packages listed in requirements.txt - A GPU, since the hosted Space uses zero-a10g hardware 1. Install the huggingface_hub package. 2. Download the Space into a local folder named LGM-mini. 3. Move into that folder. 4. Install gradio at version 5.49.1. 5. Install the packages listed in requirements.txt. 6. Start the app. ```sh pip install -U huggingface_hub hf download dylanebert/LGM-mini --repo-type space --local-dir LGM-mini cd LGM-mini pip install gradio==5.49.1 pip install -r requirements.txt python app.py ``` How to use it: Open the Space's page, or start the app locally with the command below. Then use the Gradio page that opens. ```sh python app.py ``` ```table Tool | What it does app.py | The main file, which starts the Gradio app requirements.txt | Lists the Python packages the app needs ``` Example: You run the download commands and then python app.py. The Gradio page opens in your browser, and you use it with a picture of your choice. For newcomers and experts: If you are new, open the Space's page and try it with one simple picture. Expect to read the page itself to learn what the controls do. If you know the field, the model list mixes LGM with ImageDream and a multi-view diffusion model, which fits a pipeline from a picture to several views and then to 3D. That is a reading of the names, not a statement in the source. ```flow Open the Space or run app.py Give the page an input The named models run on a GPU The page shows the result ``` Good to know: - The Space has no description, so what it returns is not documented - The hosted version uses a GPU, so a local run needs capable hardware - License: mit - Cost to run: none named - Data it reaches: the inputs you give the page, and the model files it names ## On Hugging Face, 13 November 2026 - Likes: 123 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/dylanebert/LGM-mini - Files: https://huggingface.co/spaces/dylanebert/LGM-mini/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [dylanebert/LGM-mini on Hugging Face](https://huggingface.co/spaces/dylanebert/LGM-mini) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | LGM-Mini (this page) | 123 | gradio | mit | 2026-05-26 | | [FLUX.1 dev](https://mindket.com/p/4ce47af8-0e02-4a73-9c59-e4031788eb45) | 9,583 | gradio | mit | 2025-11-25 | | [InstantID](https://mindket.com/p/54fcb36c-756a-4797-80c1-05779f87ebbd) | 3,659 | gradio | apache-2.0 | 2025-08-26 | | [Chat With Janus-Pro-7B](https://mindket.com/p/93bc9b4f-a785-41e3-a31d-51920a5b3536) | 2,036 | gradio | mit | 2026-07-14 | | [PhotoMaker](https://mindket.com/p/b3e336b4-4a67-4e52-8c2e-1e94d392ac71) | 1,960 | gradio | apache-2.0 | 2025-08-28 | | [Z Image Turbo](https://mindket.com/p/adfd87b7-3f3e-405e-95c8-1957bc0da52a) | 1,940 | gradio | apache-2.0 | 2026-05-22 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-05-26 - First published: 2024-02-21 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open dylanebert/LGM-mini on Hugging Face](https://huggingface.co/spaces/dylanebert/LGM-mini) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/d1348a8b-2e21-425e-88dd-d182a1ce8b68) - [Its page on Mindket](https://mindket.com/p/d1348a8b-2e21-425e-88dd-d182a1ce8b68)