avin_regmi

6 ms·

1.
Show HN: Clean, high-quality AI image generation(shutterly.co)
4 points by avin_regmi 1y ago|1 comments
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Show HN: Labelur – Text classifier without training data
2 points by avin_regmi 6y ago|0 comments
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by avin_regmi 6y ago
That's really good to know. Why do SEOs use this? Would you be able to connect them with me?
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by avin_regmi 6y ago
This requires you to upload a labeled dataset. My idea was more of like you enter instances of text without label and ML model will label those texts for you.
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Ask HN: Do you think this is a good startup idea?
9 points by avin_regmi 6y ago|18 comments
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Google claims its quantum computer can do the impossible in 200 seconds(cnn.com)
2 points by avin_regmi 7y ago|0 comments
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by avin_regmi 7y ago
This looks really good. I would like to speak with you. Do you have an email I can contact you?
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by avin_regmi 7y ago
what about playing with different hyperparameters? I always found that time consuming? What do you guys think?
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by avin_regmi 7y ago
Thanks for the clarification.
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by avin_regmi 7y ago
This looks interesting but who are your targeted customers? Are you building this for developers? Also what kind of models do you support?
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Show HN: Panini AI – Serve ML/DL Models in Few Minutes(panini.ai)
11 points by avin_regmi 7y ago|0 comments
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Ask HN: What do you guys think about Ludwig from Uber?
1 points by avin_regmi 8y ago|0 comments
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by avin_regmi 8y ago
I'll take your feedback into consideration :)
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by avin_regmi 8y ago
Our platform is free for the beta users to try it with limit of 2GB per model. We are just starting and we haven't decided on our business model yet. If a user downloads panini to their private server and use it that will always be fre
15.
by avin_regmi 8y ago
It really depends on the application. Such as content recommendation, prediction of popular items are requested frequently. We maintain prediction cache so we can serve the frequent cache without passing into the model. We also use cache fo
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by avin_regmi 8y ago
What are you currently using to server ML models?
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by avin_regmi 8y ago
Optimized TF serving would perform similarly to Panini however, it's really hard to find good documentation on optimizing TF serving compilation parameters. Panini automatically finds the right batch size to maximize the throughput and
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by avin_regmi 8y ago
I would love it if you try and provide me some feedback.
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by avin_regmi 8y ago
Sorry, I should've been more clear. Both predictions for TF serving and panini serving was done in a single thread in the same specification machine. We used a simple model for image classification of CIFAR dataset. Roughly, 500 predic
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by avin_regmi 8y ago
1. Caching the input will save lots of time. Inputs are not unique each time. In a production environment, lots of inputs are the same. Many platforms in fact will do caching such as Algorithmia, TF Serving, and Sagemaker. If a time to do a
21.
by avin_regmi 8y ago
Sorry, I should've been more clear. Both predictions for TF serving and panini serving was done in a single thread in the same specification machine. We used a simple model for image classification of CIFAR dataset. Roughly, 500 predic
22.
by avin_regmi 8y ago
Hey, both prediction for TF serving and panini serving was done in a single thread in the same specification machine. We used a simple model for image classification of CIFAR dataset. Roughly, 500 predictions were made for panini and 200 pr
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by avin_regmi 8y ago
Hey, you don't have to deploy in GKE and it's not GKE that makes it faster. We also give you option to deploy in your own private Kubernetes via Helm or private server via DockerHub. GKE may not be the right option for you dependi
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Show HN: Panini AI – A platform to serve ML/DL models at low latency(panini.ai)
29 points by avin_regmi 8y ago|24 comments
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by avin_regmi 8y ago
How big is low latency issue for you? What happens if it's more than 100ms? Also we do offer our software to be deployed in your kubernetes couster via helm.
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Ask HN: What are you using to serve ML models in low latency?
2 points by avin_regmi 8y ago|2 comments
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by avin_regmi 8y ago
Inferring the model with Flask is slow and requires custom code for caching and batching. Scaling in multiple machines using Flask also causes many complications. To address these issues, we have developed Panini. https://www.pan
28.
Deploy SciKit Learn Model into Kubernetes Production in Under 2 Minutes(medium.com)
1 points by avin_regmi 8y ago|0 comments
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Serve ML/DL models at low latency(medium.com)
2 points by avin_regmi 8y ago|0 comments
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The easiest way to deploy ML models to production
1 points by avin_regmi 8y ago|0 comments

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