huggingface_hub VS Sentry

Something to think about:

https://github.com/huggingface/huggingface_hub

Yes! We have a well documented Python library (https://github.com/huggingface/huggingface_hub) and public endpoints (https://huggingface.co/docs/hub/api#endpoints-table) you can use to retrieve information about the models and potentially build UIs with specific use cases in mind

i think if you search for pixel art here there are some models worth checking out: https://huggingface.co/

I received another error saying OSError: We couldn't connect to 'https://huggingface.co' to load this model, couldn't find it in the cached files and it looks like ./vae is not the path to a directory containing a file named diffusion_pytorch_model.bin

I plan to release it on https://huggingface.co/, where all this cool AI stuff is available for free for everyone that wishes to try it.

For this I used mainly the chainner application with models from here but I also used the google colab automatic1111 stable diffusion webui (for example for Lanczos) and also spaces fromhuggingface like this one or then from the replicate.com website super resolution collection.

you will now need to create a huggingface account ( https://huggingface.co/) if you haven't already. When you have, go here and accept the terms, https://huggingface.co/runwayml/stable-diffusion-v1-5. When you have done both, click on your profile icon and go to settings. Click access tokens and then create token, name it whatever you want, select "write". When you are finished with all this, then you can run the next cell which is the hugging face cell. It will ask for a token, you copy and paste what you just created.

First, sign up for a free account at https://sentry.io. Create a new project and make note of your DSN (Data Source Name).

Using APM tools like NewRelic, Sentry, Datadog, etc to monitor the performance of your application and while you're on it, they can help you identify N+1 queries.

However, ensuring the reliability and performance of your Next.js app is equally crucial. That’s where Sentry comes into play. Combined with Sentry, an industry-leading error monitoring platform, Next.js empowers developers to proactively identify and resolve issues that may arise in their applications. In this article, we’ll explore how to integrate Sentry into your Next.js project for effective error monitoring and performance optimization.

Sentry: Error monitoring for applications, including APIs. Also offers application performance monitoring (APM).

Indeed, webapps are not immune to distribution problems. Wayward and invasive browser extensions are a clear threat, as are 3rd-party dependencies (and their dependencies) loaded at runtime. Which is why companies like https://sentry.io exist. I think the difference is that webapps are "distributable by default" and it takes real work to break this. Versus having local desktop apps which require work to distribute. A potent example of the power of defaults.

Sentry produces nothing of value? You don't value an open source error tracking and performance monitoring platform? https://github.com/getsentry/sentry

> You invent something, and then immediately turn it into a cheap commodity by releasing it for free.

Exactly. A 71-line python script https://github.com/getsentry/sentry/commit/3c2e87573d3bd16f6... was groundbreaking when it came out and the fact that it springboarded into a startup is commendable.

sentry.io: 5

Sentry - Open Source Alternative For Error Tracking

11. Sentry