Where communities thrive


  • Join over 1.5M+ people
  • Join over 100K+ communities
  • Free without limits
  • Create your own community
People
Activity
    baaastijn
    @baaastijn
    i fw the issue to the team
    also, are you looking for specific AI models ?
    wingtkw-school
    @wingtkw-school
    Yes I am trying to make a music rhythm game in unity that allows user to import their own music and selects what kind of instruments to be used in generating the beat map for my final year project
    what i plan to do is to adopt an audio separation AI model to separation the audio file into soundtracks of different instruments first, then applying fourier transform to find the beats
    I have done some research online and seems like the Spleeter API will help in my project. If there's other AI model that can help, I would love to try it out as well.
    I have already subscribed to the API and authorize it with my apiKeys before launching the default swagger example online, but I got 504 Gateway Timeout
    I'm still a newbie to API so may be I haven't set up the thing correctly
    baaastijn
    @baaastijn
    thx for your explanations :) no that’s a issue on our side sorry for that
    we now have a solution called ML Serving where you can deploy your own models and get and API endpoint, and also find pre-trained ones, but Spleeter is not implemented yet
    wingtkw-school
    @wingtkw-school
    Oh ok
    Thank you for your prompt reply :) Looking forward to this ~
    Nicocg70
    @NicoCG70_twitter
    Hello. Some troubles with DeOldify ?
    Nicocg70
    @NicoCG70_twitter
    I confirm, direct access with curl to DeOldify doesn't work. Someone to confirm or fix it ?
    Nicocg70
    @NicoCG70_twitter
    Error 504 / Error: Gateway Timeout
    Nicocg70
    @NicoCG70_twitter
    @baaastijn maybe ?
    Nicocg70
    @NicoCG70_twitter
    I confirm the problem today
    baaastijn
    @baaastijn
    Hello @NicoCG70_twitter sorry for that
    to be fully transparent our team is focused to release a new service (AI training / allowing your t run training jobs on multiple GPU easily) for the end of the month
    i will ask them to take a look but i don’t have an ETA to fix it
    Nicocg70
    @NicoCG70_twitter
    so, bad news :\ I stay tuned... Last time, I remember it was easy to fix. thx
    Nicocg70
    @NicoCG70_twitter
    Some returns by your team ? @baaastijn
    baaastijn
    @baaastijn
    sorry no, it will not be for today sadly
    Nicocg70
    @NicoCG70_twitter
    ouch. Does it mean it could be fixed after more than the next week ?
    baaastijn
    @baaastijn
    sorry i don’t have an exact ETA, we will do our besT. Our goal is to move these models to our new platform, ML Serving https://docs.ovh.com/gb/en/ml-serving/
    it was not a high priority but we will see what can be done quickly
    if you have very few pictures to colorize, you can use Deoldify here : https://www.myheritage.fr/incolor @NicoCG70_twitter
    Nicocg70
    @NicoCG70_twitter
    ok thx, I need the API for an app
    Nicocg70
    @NicoCG70_twitter
    @baaastijn any hope for this week ? or definitely not ?
    baaastijn
    @baaastijn
    Hello @NicoCG70_twitter, sadly not for this week. We started the migration of the AI models to ML Serving and we expect +- 3 weeks of work
    after that, we will have a production-ready platform fall many AI models
    this current marketplace was free but not production-ready, we want improve the experience
    Nicocg70
    @NicoCG70_twitter
    If I understand the service is down (ok it's not for production, no worry) and the new platform will sell a production environnement with this kind of services ? but now, between the two, there is no solution ? m'i wright ?
    baaastijn
    @baaastijn
    almost right : the new platform is already here, with abilities to deply pre-trained models OR your own models
    but so far Deoldify is missing
    alternative via API if you are stuck
    GitHub project for DeOldify : https://github.com/jantic/DeOldify
    Nicocg70
    @NicoCG70_twitter
    You could say that before even if it was an experimental platform :\
    baaastijn
    @baaastijn

    Hello there !

    We are really glad to announce the launch of OVHcloud AI Training as a paid beta, fully integrated in our public cloud openstack ecosystem.

    You may know that data-related projects are booming, and we want to provide you all the required tools to build you own data and AI dreamed platform.

    Since 2 years we added new services (Apache Hadoop big data clusters, Data processing powered by Apache Spark, ML Serving to deploy models in production, …).

    Now, with AI Training, we simplify the life of data scientists and data engineers for neural network trainings over GPUs.

    You just have to push your code in a docker and your data on Object Storage and the platform takes care of the rest (data sync, workload deployment, user management, ...).

    If you don't know docker, it doesn't matter, you can use our prebuilt images with your favorite framework (HuggingFace, Pytorch, Tensorflow, MXNet, Fast.ai, ...) with JupyterLab notebooks and VScode.

    All of that with as always, a simple and nice pricing : 1.75€ /hour /GPU NVIDIA V100s (more flavors to come…)

    What does it solve ? lot of things ! easiness to scale, orchestration, no more infrastructure to manage, cost control, … focus on code 😊

    Don’t hesitate to try it out, to share feedback or questions ! it’s on your Public Cloud control panel (AI training in left menu) or via CLI

    Product page : https://www.ovhcloud.com/en/public-cloud/ai-training/
    Documentation : https://docs.ovh.com/gb/en/ai-training/
    Roadmap : https://github.com/ovh/public-cloud-roadmap/projects/2

    Have a good day !

    Sriharsh Bhyravajjula
    @darthbhyrava

    Hello!

    My company is already using OVH servers on the cloud, and we're really interested in ML Serving, too. Could someone let me know what GPUs the ml1-*-standard nodes come with?

    baaastijn
    @baaastijn
    hello @darthbhyrava sorry for the delay
    we do not provide GPU on ML serving so far.
    we are refactoring the backend to provide exact same flavors as you can find in AI Training
    in the neat future GPU will be « NVIDIA V100s » for serving :)
    PS : if you have a bit of time, you may try this alternative : you build a docker image with you model and an api inside, with flask for example, and you deploy it via AI TRaining. example tutorial : https://github.com/christophe-rannou/sample_vision_api_yolov4