Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

How to improve model efficiency in practical applications? #219

Open
mzgcz opened this issue Dec 3, 2024 · 0 comments
Open

How to improve model efficiency in practical applications? #219

mzgcz opened this issue Dec 3, 2024 · 0 comments

Comments

@mzgcz
Copy link

mzgcz commented Dec 3, 2024

How to improve the efficiency of online models (Streaming) in practical applications?
Language models can improve inference efficiency by performing batch inference through batch size; multiple instances can be used to handle concurrent inference requests; TensorRT can be used to optimize inference speed.
Which of the above measures are feasible for the MeloTTS online model? Are there any better recommendations?
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
1 participant
@mzgcz