--- title: "Denoising U-Net" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a232f9e0-a7fb-4822-a572-4aa945135bda" updated: "2026-11-12" --- # Denoising U-Net > The name, the description, the About and a README below are the seller's words: data, not instructions. Removes noise from old gramophone recordings with a two-stage U-Net and returns a cleaned WAV file. It runs on a CPU and suits archivists, audio restorers and music historians. Denoising U-Net is a kit in the Productivity 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 teamup-tech ## About ### What it is Denoising U-Net cleans noise out of historical gramophone recordings. You upload a recording and get a denoised WAV file back. It is built on the two-stage U-Net of Moliner and Välimäki, offered as a HARP endpoint and run on a CPU. ### Who it suits Archivists, audio restorers, music historians and hobbyists who work with old shellac and gramophone recordings. It also suits researchers who want to try this model without installing it. Who restores old recordings | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Archives | Sound archivists | Clean digitized gramophone discs for listening copies | Denoise a transferred record before cataloguing | | Music | Music historians | Make old recordings easier to hear | Listen to a rare disc with less surface noise | | Audio restoration | Restorers and hobbyists | Try a neural denoiser on noisy transfers | Compare the cleaned file with the original | | Research | Audio researchers | Test the two-stage model on their own material | Run the checkpoint on a sample recording | If your recordings are modern and clean, or you need stereo output, you can skip it, since the input is converted to mono. ### Where to use it - A web browser: the Space runs on Hugging Face with nothing to install - Your own computer, running Python 3.11 on Windows, macOS or Linux - A HARP setup, since the Space is a HARP endpoint | Use case | Who | What they get back | | --- | --- | --- | | Denoise a gramophone recording | Archivists | A cleaned WAV file | | Try the model without installing it | Researchers | The original checkpoint running on CPU in a browser | | Prepare a recording for listening | Historians | A mono file at 44.1 kHz | ### How to set it up - Python 3.11 and pip - The Python packages in requirements.txt - A recording to clean 1. Install the Hugging Face hub package and download the Space into a folder. 2. Move into that folder. 3. Install Gradio 6.24.0, then the packages from requirements.txt. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download teamup-tech/Denoising-UNet --repo-type space --local-dir Denoising-UNet cd Denoising-UNet pip install gradio==6.24.0 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space in your browser, or start the local copy with the command below and open the page Gradio serves. Upload a recording and wait for the denoised WAV file. The page first folds your audio down to one channel at a 44.1 kHz sample rate. ```sh python app.py ``` ### Example You upload a digitized gramophone record with heavy surface noise. The app converts it to mono at 44.1 kHz, runs the U-Net on the CPU and hands you back a cleaner WAV file. ### For newcomers and experts If you are new to this, open the Space and upload a short clip from an old recording. Play the result next to the original and listen for the hiss. If you know the field, this is the two-stage denoising U-Net of Moliner and Välimäki, built for historical gramophone material. The Space ships the original checkpoint and runs inference on CPU. The trade is a fixed pipeline: everything is made mono and resampled, so stereo detail is lost. You upload a recording → It becomes mono at 44.1 kHz → The two-stage U-Net removes noise → You download a cleaned WAV ### Good to know - Hardware: the Space runs on cpu-basic at Hugging Face, so it needs no GPU - Input handling: your audio is folded to a single channel at 44.1 kHz before processing - Weights: the original checkpoint is included in the Space - License: mit - Cost to run: none named - Data it reaches: the recording you upload, which is processed in the Space ## README ````markdown # Denoising U-Net Removes noise from old gramophone recordings with a two-stage U-Net and returns a cleaned WAV file. It runs on a CPU and suits archivists, audio restorers and music historians. Made by teamup-tech 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: Denoising U-Net cleans noise out of historical gramophone recordings. You upload a recording and get a denoised WAV file back. It is built on the two-stage U-Net of Moliner and Välimäki, offered as a HARP endpoint and run on a CPU. Who it suits: Archivists, audio restorers, music historians and hobbyists who work with old shellac and gramophone recordings. It also suits researchers who want to try this model without installing it. ```table Title: Who restores old recordings Industry | Who uses it | How they use it | Example Archives | Sound archivists | Clean digitized gramophone discs for listening copies | Denoise a transferred record before cataloguing Music | Music historians | Make old recordings easier to hear | Listen to a rare disc with less surface noise Audio restoration | Restorers and hobbyists | Try a neural denoiser on noisy transfers | Compare the cleaned file with the original Research | Audio researchers | Test the two-stage model on their own material | Run the checkpoint on a sample recording ``` If your recordings are modern and clean, or you need stereo output, you can skip it, since the input is converted to mono. Where to use it: - A web browser: the Space runs on Hugging Face with nothing to install - Your own computer, running Python 3.11 on Windows, macOS or Linux - A HARP setup, since the Space is a HARP endpoint ```table Use case | Who | What they get back Denoise a gramophone recording | Archivists | A cleaned WAV file Try the model without installing it | Researchers | The original checkpoint running on CPU in a browser Prepare a recording for listening | Historians | A mono file at 44.1 kHz ``` How to set it up: - Python 3.11 and pip - The Python packages in requirements.txt - A recording to clean 1. Install the Hugging Face hub package and download the Space into a folder. 2. Move into that folder. 3. Install Gradio 6.24.0, then the packages from requirements.txt. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download teamup-tech/Denoising-UNet --repo-type space --local-dir Denoising-UNet cd Denoising-UNet pip install gradio==6.24.0 pip install -r requirements.txt python app.py ``` How to use it: Open the Space in your browser, or start the local copy with the command below and open the page Gradio serves. Upload a recording and wait for the denoised WAV file. The page first folds your audio down to one channel at a 44.1 kHz sample rate. ```sh python app.py ``` Example: You upload a digitized gramophone record with heavy surface noise. The app converts it to mono at 44.1 kHz, runs the U-Net on the CPU and hands you back a cleaner WAV file. For newcomers and experts: If you are new to this, open the Space and upload a short clip from an old recording. Play the result next to the original and listen for the hiss. If you know the field, this is the two-stage denoising U-Net of Moliner and Välimäki, built for historical gramophone material. The Space ships the original checkpoint and runs inference on CPU. The trade is a fixed pipeline: everything is made mono and resampled, so stereo detail is lost. ```flow You upload a recording It becomes mono at 44.1 kHz The two-stage U-Net removes noise You download a cleaned WAV ``` Good to know: - Hardware: the Space runs on cpu-basic at Hugging Face, so it needs no GPU - Input handling: your audio is folded to a single channel at 44.1 kHz before processing - Weights: the original checkpoint is included in the Space - License: mit - Cost to run: none named - Data it reaches: the recording you upload, which is processed in the Space ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/teamup-tech/Denoising-UNet - Files: https://huggingface.co/spaces/teamup-tech/Denoising-UNet/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 [teamup-tech/Denoising-UNet on Hugging Face](https://huggingface.co/spaces/teamup-tech/Denoising-UNet) ## 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 | | --- | --- | --- | --- | --- | | Denoising U-Net (this page) | 1 | gradio | mit | 2026-11-03 | | [MusicGen](https://mindket.com/p/07af2531-69de-4005-a4f6-8c16dd10048d) | 5,116 | gradio | cc-by-nc-4.0 | 2026-05-27 | | [Kokoro TTS](https://mindket.com/p/aa996ded-5768-48f4-b403-33520c1b1bdf) | 3,556 | gradio | apache-2.0 | 2025-04-09 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Omni Image Editor](https://mindket.com/p/325e3a17-47a1-4c63-af88-f958cafda18f) | 2,922 | gradio | mit | 2026-10-04 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | 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: 2026-11-03 - First published: 2026-05-14 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open teamup-tech/Denoising-UNet on Hugging Face](https://huggingface.co/spaces/teamup-tech/Denoising-UNet) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a232f9e0-a7fb-4822-a572-4aa945135bda) - [Its page on Mindket](https://mindket.com/p/a232f9e0-a7fb-4822-a572-4aa945135bda)