Finetune CLAP on {audio, text} pairs
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 2.3k
- Forks
- 213
- PR merge metrics
- No merged PRs in 30d
Description
Hello!
Suppose I have a dataset of {audio, text} pairs. I would now like to finetune CLAP on this audio subset. Do you have any tips for getting started with such a task? Would continuing the training from a checkpoint with a smaller learning rate be somewhat of a good start? Do you have scripts that allow to do something similar?
Thanks
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
No files, tests, scripts, or entry points are identified in the issue. Start by locating any existing training and checkpoint-loading entry points, then determine what a supported audio-text fine-tuning workflow would require; done would mean a documented, runnable path for the described dataset.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- audio-video-rtc, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100