--- title: "BiomedicalNERModel" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/8ff611ce-dfc6-4b1e-8472-9a2d47969bc4" updated: "2026-11-12" --- # BiomedicalNERModel > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio demo for named entity recognition in biomedical text, built around the ajitrajasekharan/biomedical model. It suits people who want to try entity tagging in a browser. BiomedicalNERModel 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 ajitrajasekharan ## About ### What it is BiomedicalNERModel is a Gradio demo on Hugging Face Spaces for named entity recognition in biomedical text. It names the ajitrajasekharan/biomedical model. The repository is small, with only a README and app.py, and the README holds just a settings pointer. ### Who it suits It suits people working with biomedical text who want to see entity tagging in a browser, and learners who want a short example of a model behind a Gradio page. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Healthcare research | Text-mining researchers | Try entity tagging on biomedical sentences | Open the Space and enter a sentence | | Life sciences | Data scientists | Read app.py to see how the model is called | Download the Space and open app.py | | Education | Instructors | Show named entity recognition on domain text | Run the demo in a lesson | Anyone who needs a production pipeline, a list of entity types or measured accuracy can skip it, since the source gives none. ### Where to use it - A web browser, straight from the Space page on Hugging Face - Windows, macOS or Linux with Python, as a local copy | Use case | Who | What they get back | | --- | --- | --- | | Tag entities in a sentence | Researchers | Entities marked in the text shown in the browser | | Study a model demo | Learners | A single app file that calls a named model | ### How to set it up Using it online needs nothing. A local copy needs these first. - Python and pip - The huggingface\_hub package, to fetch the files - Gradio, which is the only package the steps install 1. Install the Hugging Face Hub package. 2. Download the Space into a folder called Bio-medical-NER-Model-Gradio-Demo. 3. Move into that folder. 4. Install Gradio. 5. Start the app. ```sh pip install -U huggingface_hub hf download ajitrajasekharan/Bio-medical-NER-Model-Gradio-Demo --repo-type space --local-dir Bio-medical-NER-Model-Gradio-Demo cd Bio-medical-NER-Model-Gradio-Demo pip install gradio python app.py ``` ### How to use it Open the Space page on Hugging Face, enter some biomedical text and read the result. For a local copy, run python app.py in the folder and open the page it starts. ### Example You paste a sentence about a drug and a disease into the text box. The app passes it to the biomedical model and shows the entities it finds in the sentence. ### For newcomers and experts If you are new, open the Space page and try one short sentence. Named entity recognition means the model marks the names of things, such as a drug or a disease, in your text. If you know the field, the source names one model, ajitrajasekharan/biomedical, and the repository has no requirements file. The steps install only Gradio, so extra packages may be needed on your machine. You enter biomedical text in the browser → app.py sends it to the named model → The tagged entities show on the page ### Good to know - The README gives no description, so what the page returns is clear only when you try it - The repository has no requirements file, so the packages app.py imports may need installing yourself - License: mit - Cost to run: none named - Data it reaches: the ajitrajasekharan/biomedical model it names ## README ````markdown # BiomedicalNERModel A Gradio demo for named entity recognition in biomedical text, built around the ajitrajasekharan/biomedical model. It suits people who want to try entity tagging in a browser. Made by ajitrajasekharan 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: BiomedicalNERModel is a Gradio demo on Hugging Face Spaces for named entity recognition in biomedical text. It names the ajitrajasekharan/biomedical model. The repository is small, with only a README and app.py, and the README holds just a settings pointer. Who it suits: It suits people working with biomedical text who want to see entity tagging in a browser, and learners who want a short example of a model behind a Gradio page. ```table Industry | Who uses it | How they use it | Example Healthcare research | Text-mining researchers | Try entity tagging on biomedical sentences | Open the Space and enter a sentence Life sciences | Data scientists | Read app.py to see how the model is called | Download the Space and open app.py Education | Instructors | Show named entity recognition on domain text | Run the demo in a lesson ``` Anyone who needs a production pipeline, a list of entity types or measured accuracy can skip it, since the source gives none. Where to use it: - A web browser, straight from the Space page on Hugging Face - Windows, macOS or Linux with Python, as a local copy ```table Use case | Who | What they get back Tag entities in a sentence | Researchers | Entities marked in the text shown in the browser Study a model demo | Learners | A single app file that calls a named model ``` How to set it up: Using it online needs nothing. A local copy needs these first. - Python and pip - The huggingface_hub package, to fetch the files - Gradio, which is the only package the steps install 1. Install the Hugging Face Hub package. 2. Download the Space into a folder called Bio-medical-NER-Model-Gradio-Demo. 3. Move into that folder. 4. Install Gradio. 5. Start the app. ```sh pip install -U huggingface_hub hf download ajitrajasekharan/Bio-medical-NER-Model-Gradio-Demo --repo-type space --local-dir Bio-medical-NER-Model-Gradio-Demo cd Bio-medical-NER-Model-Gradio-Demo pip install gradio python app.py ``` How to use it: Open the Space page on Hugging Face, enter some biomedical text and read the result. For a local copy, run python app.py in the folder and open the page it starts. Example: You paste a sentence about a drug and a disease into the text box. The app passes it to the biomedical model and shows the entities it finds in the sentence. For newcomers and experts: If you are new, open the Space page and try one short sentence. Named entity recognition means the model marks the names of things, such as a drug or a disease, in your text. If you know the field, the source names one model, ajitrajasekharan/biomedical, and the repository has no requirements file. The steps install only Gradio, so extra packages may be needed on your machine. ```flow You enter biomedical text in the browser app.py sends it to the named model The tagged entities show on the page ``` Good to know: - The README gives no description, so what the page returns is clear only when you try it - The repository has no requirements file, so the packages app.py imports may need installing yourself - License: mit - Cost to run: none named - Data it reaches: the ajitrajasekharan/biomedical model it names ## On Hugging Face, 13 November 2026 - Likes: 5 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/ajitrajasekharan/Bio-medical-NER-Model-Gradio-Demo - Files: https://huggingface.co/spaces/ajitrajasekharan/Bio-medical-NER-Model-Gradio-Demo/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 [ajitrajasekharan/Bio-medical-NER-Model-Gradio-Demo on Hugging Face](https://huggingface.co/spaces/ajitrajasekharan/Bio-medical-NER-Model-Gradio-Demo) ## 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 | | --- | --- | --- | --- | --- | | BiomedicalNERModel (this page) | 5 | gradio | mit | 2022-01-30 | | [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: 2022-01-30 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open ajitrajasekharan/Bio-medical-NER-Model-Gradio-Demo on Hugging Face](https://huggingface.co/spaces/ajitrajasekharan/Bio-medical-NER-Model-Gradio-Demo) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/8ff611ce-dfc6-4b1e-8472-9a2d47969bc4) - [Its page on Mindket](https://mindket.com/p/8ff611ce-dfc6-4b1e-8472-9a2d47969bc4)