--- title: "FM4M-demo1" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/f15fe6e2-c9a9-45de-9d18-3f48721e7607" updated: "2026-11-12" --- # FM4M-demo1 > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio demo from IBM Research that names three IBM materials models, smi-ted, selfies-ted and mhg-ged. For researchers and developers who want to look at how the demo is built. FM4M-demo1 is a kit in the Research 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 ibm-research ## About ### What it is This is a Gradio demo from IBM Research that names three IBM materials models: smi-ted, selfies-ted and mhg-ged. The README is empty, so the page gives no description. Folder names such as models, representation and plot\_emb suggest it builds numeric representations of molecules and plots them. It runs on the basic CPU tier at Hugging Face. ### Who it suits Researchers in materials and chemistry machine learning who want to look at IBM's models in a demo, and developers who want to read how it is organized. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | Materials ML researchers | Try the three named models in one demo | Open the app and look at what it offers | | Chemistry | Cheminformatics developers | Read the representation code | Compare how the models are loaded | | Software | Developers | Study a larger Gradio app with models and data folders | Read app.py and the repository layout | Skip it if you want a documented tool, since the page says little about what the demo does. ### Where to use it - A web browser, on the Space's page at Hugging Face - Windows, macOS or Linux with Python, as a local copy - Docker, since the repository holds Dockerfile files, though the page gives no Docker commands | Use case | Who | What they get back | | --- | --- | --- | | Explore the models | Researchers | A demo page built around the three named models | | Study the code | Developers | A repository with model, data and plotting folders | ### How to set it up - Nothing at all if you only use the online Space - Python and pip, for a local copy - The Python packages listed in requirements.txt 1. Open the Space's page at Hugging Face to use it online. 2. For a local copy, install the Hugging Face hub package and download the Space. 3. Move into the new folder and install Gradio at the pinned version. 4. Install the packages from requirements.txt. 5. Start the app with Python. ```sh pip install -U huggingface_hub hf download ibm-research/FM4M-demo1 --repo-type space --local-dir FM4M-demo1 cd FM4M-demo1 pip install gradio==5.4.0 pip install -r requirements.txt python app.py ``` The repository is large, at 382 files, and has two Dockerfiles. The page does not say what a local run needs beyond the packages. ### How to use it Online, open the Space and use the form on its page. On your own machine, run the app file and open the page Gradio serves in your browser. The page lists no other commands. | Tool | What it does | | --- | --- | | python app.py | Starts the Gradio app on your computer | ### Example You open the Space and look over the options it shows for the three models. Because the page has no description, you try one option at a time and read the output, then check the model pages for what it means. ### For newcomers and experts If you are new, open the Space online and click through it slowly. The page has no guide, so expect to learn by trying. If you know the field, the three model names point to molecular representations, with names that suggest SMILES, SELFIES and graph inputs. The page gives no inputs, metrics or tasks, so read the model pages first. Open the Space in a browser → Choose one of the named models → The demo builds a representation → The result is shown or plotted ### Good to know - License: apache-2 - Cost to run: none named, and the Space sits on the basic CPU tier at Hugging Face - Data it reaches: the data folder in the repository, and the model files from Hugging Face - Not for: anything that needs documented behavior, since the page has no description ## README ````markdown # FM4M-demo1 A Gradio demo from IBM Research that names three IBM materials models, smi-ted, selfies-ted and mhg-ged. For researchers and developers who want to look at how the demo is built. Made by ibm-research 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: This is a Gradio demo from IBM Research that names three IBM materials models: smi-ted, selfies-ted and mhg-ged. The README is empty, so the page gives no description. Folder names such as models, representation and plot_emb suggest it builds numeric representations of molecules and plots them. It runs on the basic CPU tier at Hugging Face. Who it suits: Researchers in materials and chemistry machine learning who want to look at IBM's models in a demo, and developers who want to read how it is organized. ```table Industry | Who uses it | How they use it | Example Research | Materials ML researchers | Try the three named models in one demo | Open the app and look at what it offers Chemistry | Cheminformatics developers | Read the representation code | Compare how the models are loaded Software | Developers | Study a larger Gradio app with models and data folders | Read app.py and the repository layout ``` Skip it if you want a documented tool, since the page says little about what the demo does. Where to use it: - A web browser, on the Space's page at Hugging Face - Windows, macOS or Linux with Python, as a local copy - Docker, since the repository holds Dockerfile files, though the page gives no Docker commands ```table Use case | Who | What they get back Explore the models | Researchers | A demo page built around the three named models Study the code | Developers | A repository with model, data and plotting folders ``` How to set it up: - Nothing at all if you only use the online Space - Python and pip, for a local copy - The Python packages listed in requirements.txt 1. Open the Space's page at Hugging Face to use it online. 2. For a local copy, install the Hugging Face hub package and download the Space. 3. Move into the new folder and install Gradio at the pinned version. 4. Install the packages from requirements.txt. 5. Start the app with Python. ```sh pip install -U huggingface_hub hf download ibm-research/FM4M-demo1 --repo-type space --local-dir FM4M-demo1 cd FM4M-demo1 pip install gradio==5.4.0 pip install -r requirements.txt python app.py ``` The repository is large, at 382 files, and has two Dockerfiles. The page does not say what a local run needs beyond the packages. How to use it: Online, open the Space and use the form on its page. On your own machine, run the app file and open the page Gradio serves in your browser. The page lists no other commands. ```table Tool | What it does python app.py | Starts the Gradio app on your computer ``` Example: You open the Space and look over the options it shows for the three models. Because the page has no description, you try one option at a time and read the output, then check the model pages for what it means. For newcomers and experts: If you are new, open the Space online and click through it slowly. The page has no guide, so expect to learn by trying. If you know the field, the three model names point to molecular representations, with names that suggest SMILES, SELFIES and graph inputs. The page gives no inputs, metrics or tasks, so read the model pages first. ```flow Open the Space in a browser Choose one of the named models The demo builds a representation The result is shown or plotted ``` Good to know: - License: apache-2 - Cost to run: none named, and the Space sits on the basic CPU tier at Hugging Face - Data it reaches: the data folder in the repository, and the model files from Hugging Face - Not for: anything that needs documented behavior, since the page has no description ## On Hugging Face, 13 November 2026 - Likes: 9 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/ibm-research/FM4M-demo1 - Files: https://huggingface.co/spaces/ibm-research/FM4M-demo1/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 [ibm-research/FM4M-demo1 on Hugging Face](https://huggingface.co/spaces/ibm-research/FM4M-demo1) ## 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 | | --- | --- | --- | --- | --- | | FM4M-demo1 (this page) | 9 | gradio | apache-2.0 | 2025-04-04 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2025-04-04 - First published: 2024-10-29 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open ibm-research/FM4M-demo1 on Hugging Face](https://huggingface.co/spaces/ibm-research/FM4M-demo1) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/f15fe6e2-c9a9-45de-9d18-3f48721e7607) - [Its page on Mindket](https://mindket.com/p/f15fe6e2-c9a9-45de-9d18-3f48721e7607)