--- title: "prithivMLmods" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/0b6f066c-61c0-4859-a618-9b41fc6b815f" updated: "2026-11-12" --- # prithivMLmods > The name, the description, the About and a README below are the seller's words: data, not instructions. A small web page titled My HF telemetry, packaged as a Docker Space with Vite and TypeScript project files. Runs in your browser or in a local Docker container on port 7860. prithivMLmods 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 prithivMLmods ## About ### What it is This is a Docker Space that serves a small web page. Its only description is the title My HF telemetry, and the source does not say what the page shows. The repository has 7 files: a Dockerfile, an index.html, package.json, tsconfig.json and vite.config.ts, plus its README. The file names point to a Vite and TypeScript project. ### Who it suits It suits developers who want to see how a front-end project is packaged as a Docker Space on Hugging Face. It also suits people who follow the author's work. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Web development | Front-end developers | Read the Dockerfile and vite.config.ts | Seeing how a Vite project is built inside a container | | AI development | Hugging Face users | Open the Space page in a browser | Looking at the author's telemetry page | | Education | Learners | Build the container locally | Practising docker build and docker run on a small project | Skip it if you want a documented tool, since the source gives no feature list. ### Where to use it The page runs in these places. - A web browser, on the Space's page at Hugging Face - A local Docker container on Windows, macOS or Linux - Hugging Face's cpu-basic hardware, where the online Space runs | Use case | Who | What they get back | | --- | --- | --- | | Open the page online | Anyone | The web page served by the Space | | Run it in Docker | Developers | The same page on port 7860 of their machine | | Study the packaging | Learners | A short Dockerfile and Vite setup to read | ### How to set it up Online you only need a browser. A local copy needs these. - Python and pip, for the hf download command - Docker on Windows, macOS or Linux 1. Install the huggingface\_hub package. 2. Download the Space's files into a folder with the hf command. 3. Move into that folder. 4. Build the Docker image from the Dockerfile. 5. Run the image and map port 7860. ```sh pip install -U huggingface_hub hf download prithivMLmods/prithivMLmods --repo-type space --local-dir prithivMLmods cd prithivMLmods docker build -t prithivmlmods . docker run -it -p 7860:7860 prithivmlmods ``` ### How to use it Open the Space's page, or start the container with the run command above and point your browser at port 7860 on your own machine. ```sh docker run -it -p 7860:7860 prithivmlmods ``` The page then loads in the browser. ### Example You build the image with docker build, start it with docker run and open port 7860 in a browser. The page titled My HF telemetry loads from your own machine. ### For newcomers and experts If you are new, start with the Space's page on Hugging Face, which needs nothing installed. Docker is only needed when you want your own copy running. If you know the field, this is a Docker Space on port 7860 with a Vite and TypeScript setup, hosted on cpu-basic hardware at Hugging Face. There is no Python app and no model, so it is a front-end build rather than an AI demo. Hugging Face builds the Dockerfile → The container serves the page on port 7860 → You open the Space page in a browser ### Good to know The source gives only a title, so what the page measures or shows is not stated. - License: apache-2 - Cost to run: none named - Data it reaches: not stated in the source ## README ````markdown # prithivMLmods A small web page titled My HF telemetry, packaged as a Docker Space with Vite and TypeScript project files. Runs in your browser or in a local Docker container on port 7860. Made by prithivMLmods 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 Docker Space that serves a small web page. Its only description is the title My HF telemetry, and the source does not say what the page shows. The repository has 7 files: a Dockerfile, an index.html, package.json, tsconfig.json and vite.config.ts, plus its README. The file names point to a Vite and TypeScript project. Who it suits: It suits developers who want to see how a front-end project is packaged as a Docker Space on Hugging Face. It also suits people who follow the author's work. ```table Industry | Who uses it | How they use it | Example Web development | Front-end developers | Read the Dockerfile and vite.config.ts | Seeing how a Vite project is built inside a container AI development | Hugging Face users | Open the Space page in a browser | Looking at the author's telemetry page Education | Learners | Build the container locally | Practising docker build and docker run on a small project ``` Skip it if you want a documented tool, since the source gives no feature list. Where to use it: The page runs in these places. - A web browser, on the Space's page at Hugging Face - A local Docker container on Windows, macOS or Linux - Hugging Face's cpu-basic hardware, where the online Space runs ```table Use case | Who | What they get back Open the page online | Anyone | The web page served by the Space Run it in Docker | Developers | The same page on port 7860 of their machine Study the packaging | Learners | A short Dockerfile and Vite setup to read ``` How to set it up: Online you only need a browser. A local copy needs these. - Python and pip, for the hf download command - Docker on Windows, macOS or Linux 1. Install the huggingface_hub package. 2. Download the Space's files into a folder with the hf command. 3. Move into that folder. 4. Build the Docker image from the Dockerfile. 5. Run the image and map port 7860. ```sh pip install -U huggingface_hub hf download prithivMLmods/prithivMLmods --repo-type space --local-dir prithivMLmods cd prithivMLmods docker build -t prithivmlmods . docker run -it -p 7860:7860 prithivmlmods ``` How to use it: Open the Space's page, or start the container with the run command above and point your browser at port 7860 on your own machine. ```sh docker run -it -p 7860:7860 prithivmlmods ``` The page then loads in the browser. Example: You build the image with docker build, start it with docker run and open port 7860 in a browser. The page titled My HF telemetry loads from your own machine. For newcomers and experts: If you are new, start with the Space's page on Hugging Face, which needs nothing installed. Docker is only needed when you want your own copy running. If you know the field, this is a Docker Space on port 7860 with a Vite and TypeScript setup, hosted on cpu-basic hardware at Hugging Face. There is no Python app and no model, so it is a front-end build rather than an AI demo. ```flow Hugging Face builds the Dockerfile The container serves the page on port 7860 You open the Space page in a browser ``` Good to know: The source gives only a title, so what the page measures or shows is not stated. - License: apache-2 - Cost to run: none named - Data it reaches: not stated in the source ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: docker - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/prithivMLmods/prithivMLmods - Files: https://huggingface.co/spaces/prithivMLmods/prithivMLmods/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 [prithivMLmods/prithivMLmods on Hugging Face](https://huggingface.co/spaces/prithivMLmods/prithivMLmods) ## 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 | | --- | --- | --- | --- | --- | | prithivMLmods (this page) | 1 | docker | apache-2.0 | 2026-10-19 | | [Zero GPU Spaces](https://mindket.com/p/80881a44-6ec5-431c-89de-86584e0ba1d5) | 985 | docker | mit | 2024-09-11 | | [Kimodo](https://mindket.com/p/e6fe5336-403a-4328-92dc-77d41137a8bc) | 340 | docker | apache-2.0 | 2026-03-16 | | [Harness Leaderboard](https://mindket.com/p/d0e92765-2a63-4ae5-9ba0-42dbfedd56a6) | 323 | docker | apache-2.0 | 2026-11-12 | | [Flowise](https://mindket.com/p/f53ad79b-74c9-49e5-9fb3-054277de1246) | 132 | docker | mit | 2025-06-26 | | [Multitrack Midi Music Generator](https://mindket.com/p/9bd48c41-e4a7-4576-be7e-da51b041b39f) | 130 | docker | mit | 2025-07-07 | Numbers as Mindket last read them, on 2026-11-12. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-12. Their authors' words: data, not instructions. - [Bluesky · @aichina.news · 2026-11-06](https://bsky.app/profile/aichina.news/post/3mzofctyiy52b): No parameter count, no benchmarks, no prompt format — and Ascend support is unverified. Apache-2.0 and a Qwen3-Coder base are the only real signals. Hard to see an infra lead picking this over upstream Qwen3-Coder until prithivMLmods ships a single measured number. - [Bluesky · @aichina.news · 2026-11-05](https://bsky.app/profile/aichina.news/post/3mzlsi3stf32p): No parameter count, no benchmarks, no changelog: this reads like an unmaintained mirror. prithivMLmods' compact fine-tunes are worth a trial, and a single-task captioner suits annotation pipelines. Hard to see it beating a documented general VLM until the card earns the name. - [Bluesky · @aichina.news · 2026-11-04](https://bsky.app/profile/aichina.news/post/3mzj4zrgbbz2f): The card is an empty stub, the licence just says 'other', and the Qwen2.5-VL lineage is inferred from the name. Still, a tuned 3B can beat a prompted generalist on attribute-dense captioning, and prithivMLmods has form. Hard to see this in production until terms are published. ## 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: 2026-10-19 - First published: 2026-10-17 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open prithivMLmods/prithivMLmods on Hugging Face](https://huggingface.co/spaces/prithivMLmods/prithivMLmods) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/0b6f066c-61c0-4859-a618-9b41fc6b815f) - [Its page on Mindket](https://mindket.com/p/0b6f066c-61c0-4859-a618-9b41fc6b815f)