nomadkaraoke / nomadkaraoke/python-audio-separator
[Feature]: Update Model and Config Repository Links (if possible)
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- Python
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Description
Description
Recently, I created two repositories for UVR configs and models:
- Repository for storing models and configs
- Repository for storing configs, model data, and a list of all publicly available models
In the second link, you can find two files: model_list_filenames.json and model_list_links.json
- The first file contains user-friendly model names and model filenames.
- The second file contains the same information but with links to the provided models and configs.
- Models are sourced from my HuggingFace repository.
- Configs are sourced from my GitHub repository.
I think this will make it much easier to edit configs and add new models.
Do you think it's possible to replace the old links with the current ones?
I haven't tried it myself yet, but I think it's a good idea since the old repository is rarely updated and doesn't add many new models. It would be better if you could add support for files from my repository. And yes, almost all the models there work fine, except those that require changes in the files bs_roformer.py and mel_band_roformer.py and the addition of new architectures.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by comparing the existing model and config link handling with the proposed model_list_filenames.json and model_list_links.json files. Check whether the listed models work without changes to bs_roformer.py or mel_band_roformer.py, and identify any new architectures that would need support. Done means the updated repositories and supported models are verified without breaking existing model downloads.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100