--- title: "Similarity Heatmap" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/bec49cc4-bb0e-4c22-b200-677f0d502b0b" updated: "2026-11-13" --- # Similarity Heatmap > The name, the description, the About and a README below are the seller's words: data, not instructions. Opens a small Streamlit app whose title points to a similarity heatmap. The listing does not say what it compares, so treat it as a demo for developers and students to open and explore. Similarity Heatmap is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by kingfisher ## About ### What it is This is a small Streamlit app from kingfisher with a single main file. Its title points to a heatmap that shows similarity. The source does not say what it compares, and it names no model. You use it in a browser, or you run a copy on your own computer. ### Who it suits It suits students and developers who want to look at a similarity heatmap demo and read how a short Streamlit app is built. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Data science students | Open a small Streamlit demo and study the page | Open the Space and look at what it shows | | Software | Python developers | Run a copy locally and read app.py | Download the Space and start it with Streamlit | | Research | Data analysts | Check whether the demo fits a similarity task | Try it on a small sample first | Skip it if you need a documented tool, because the source says little about what the app does. ### Where to use it - A web browser: go to the Space on Hugging Face and try it with no install - Windows, macOS or Linux: run a copy with Python | Use case | Who | What they get back | | --- | --- | --- | | Explore the demo | Students | A page whose title points to a similarity heatmap | | Read the code | Developers | A short app.py behind a Streamlit page | | Adapt the app | Analysts | A starting point for their own comparison view | ### How to set it up You need a few things in place first. - Python with pip, on Windows, macOS or Linux - An internet connection to fetch the files from Hugging Face 1. Install the Hugging Face hub package. 2. Download the Space into a local folder. 3. Move into that folder. 4. Install Streamlit and the packages listed in requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download kingfisher/similarity-heatmap --repo-type space --local-dir similarity-heatmap cd similarity-heatmap pip install streamlit pip install -r requirements.txt streamlit run app.py ``` ### How to use it Online, use the Streamlit page the Space shows. On your own computer, start the app with the command below and open the page it serves in your browser. ```sh streamlit run app.py ``` ### Example You run streamlit run app.py inside the project folder and open the page it serves. The page then shows the similarity view the app was written to draw. ### For newcomers and experts If this is new to you, start online. Go to the Space and look around before you install anything. Reading the short app.py afterward shows how it works. If you know the field, note that the repository holds only a README, app.py and requirements.txt. The source names no model, no data set and no similarity measure, so read app.py to find out what it computes. Open the Space or run streamlit → The Streamlit page loads → You give it its inputs → The app computes similarity → A heatmap appears on the page ### Good to know The source gives no details on inputs, method or accuracy, so read the code before you rely on the output. - License: cc-by-nc-sa-4 - Cost to run: none named, no API key, account or paid service - Data it reaches: the files in the repository, with no outside account or web service listed ## README ````markdown # Similarity Heatmap Opens a small Streamlit app whose title points to a similarity heatmap. The listing does not say what it compares, so treat it as a demo for developers and students to open and explore. Made by kingfisher 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 small Streamlit app from kingfisher with a single main file. Its title points to a heatmap that shows similarity. The source does not say what it compares, and it names no model. You use it in a browser, or you run a copy on your own computer. Who it suits: It suits students and developers who want to look at a similarity heatmap demo and read how a short Streamlit app is built. ```table Industry | Who uses it | How they use it | Example Education | Data science students | Open a small Streamlit demo and study the page | Open the Space and look at what it shows Software | Python developers | Run a copy locally and read app.py | Download the Space and start it with Streamlit Research | Data analysts | Check whether the demo fits a similarity task | Try it on a small sample first ``` Skip it if you need a documented tool, because the source says little about what the app does. Where to use it: - A web browser: go to the Space on Hugging Face and try it with no install - Windows, macOS or Linux: run a copy with Python ```table Use case | Who | What they get back Explore the demo | Students | A page whose title points to a similarity heatmap Read the code | Developers | A short app.py behind a Streamlit page Adapt the app | Analysts | A starting point for their own comparison view ``` How to set it up: You need a few things in place first. - Python with pip, on Windows, macOS or Linux - An internet connection to fetch the files from Hugging Face 1. Install the Hugging Face hub package. 2. Download the Space into a local folder. 3. Move into that folder. 4. Install Streamlit and the packages listed in requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download kingfisher/similarity-heatmap --repo-type space --local-dir similarity-heatmap cd similarity-heatmap pip install streamlit pip install -r requirements.txt streamlit run app.py ``` How to use it: Online, use the Streamlit page the Space shows. On your own computer, start the app with the command below and open the page it serves in your browser. ```sh streamlit run app.py ``` Example: You run streamlit run app.py inside the project folder and open the page it serves. The page then shows the similarity view the app was written to draw. For newcomers and experts: If this is new to you, start online. Go to the Space and look around before you install anything. Reading the short app.py afterward shows how it works. If you know the field, note that the repository holds only a README, app.py and requirements.txt. The source names no model, no data set and no similarity measure, so read app.py to find out what it computes. ```flow Open the Space or run streamlit The Streamlit page loads You give it its inputs The app computes similarity A heatmap appears on the page ``` Good to know: The source gives no details on inputs, method or accuracy, so read the code before you rely on the output. - License: cc-by-nc-sa-4 - Cost to run: none named, no API key, account or paid service - Data it reaches: the files in the repository, with no outside account or web service listed ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: streamlit - License: cc-by-nc-sa-4.0 ## Links - Space: https://huggingface.co/spaces/kingfisher/similarity-heatmap - Files: https://huggingface.co/spaces/kingfisher/similarity-heatmap/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 [kingfisher/similarity-heatmap on Hugging Face](https://huggingface.co/spaces/kingfisher/similarity-heatmap) ## 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 | | --- | --- | --- | --- | --- | | Similarity Heatmap (this page) | 1 | streamlit | cc-by-nc-sa-4.0 | 2022-02-15 | | [AI Phone Leaderboard](https://mindket.com/p/c50d4420-a218-400f-917a-9fa39c2d8007) | 127 | streamlit | mit | 2026-02-04 | | [fev-bench](https://mindket.com/p/aed1efeb-102a-49fd-b48b-0e7131fb1d85) | 72 | docker | apache-2.0 | 2026-11-09 | | [Outsmart](https://mindket.com/p/bc535e3d-8da3-4481-bb74-8405891098d4) | 62 | streamlit | mit | 2026-10-21 | | [HF BERTopic](https://mindket.com/p/6ea227ee-d2c5-4685-886d-6070ad67ac1f) | 24 | streamlit | mit | 2026-08-02 | | [HF SHAP](https://mindket.com/p/aa7ec1ee-7a27-4fe5-9191-d22a0af5d958) | 8 | streamlit | mit | 2026-08-02 | 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: 2022-02-15 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open kingfisher/similarity-heatmap on Hugging Face](https://huggingface.co/spaces/kingfisher/similarity-heatmap) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/bec49cc4-bb0e-4c22-b200-677f0d502b0b) - [Its page on Mindket](https://mindket.com/p/bec49cc4-bb0e-4c22-b200-677f0d502b0b)