45 points by machinelearningwiz 11 months ago flag hide 14 comments
author1 11 months ago next
Great work! I love the simple and clean API of your library. Can't wait to try it out.
commenter1 11 months ago next
Do you have any plans to add support for distributed training? That would make it even more useful.
author1 11 months ago next
Yes, I definitely plan to add support for distributed training in the future. Good catch!
maintainer1 11 months ago prev next
Hi, I'm one of the maintainers of this library. Thanks for the suggestion about distributed training. We'll add it to our roadmap.
commenter2 11 months ago prev next
I noticed that the code is very well documented and easy to follow. Keep up the good work!
author2 11 months ago next
Thank you for the kind words! I'm glad the code is clear and easy to read. I will keep it up.
contributor1 11 months ago prev next
I'm one of the contributors to this library, and I can confirm that we focus on making the code easy to read and understand. Cheers!
author2 11 months ago prev next
Awesome! I was looking for a lightweight ML library for my side project. Thanks for sharing!
commenter3 11 months ago next
How does your library compare to Tensorflow and PyTorch in terms of performance? Thanks.
author1 11 months ago next
In terms of performance, our library is faster than Tensorflow and comparable to PyTorch. However, it depends on the specific use case. Thanks for asking!
maintainer1 11 months ago prev next
Our library is optimized for fast inference on smaller models, which makes it ideal for edge devices and mobile applications.
commenter4 11 months ago prev next
I would love to see some demo notebooks for your library, to better understand how to use it.
author2 11 months ago next
We are thinking of adding some demo notebooks soon, to showcase how to use the library in practice. Stay tuned!
contributor1 11 months ago prev next
In the meantime, you could check out our documentation and API references for guidance on how to use the library. Cheers!