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Show HN: GUIs for Faster ML Prototyping and Sharing

85 points by aliabd 6y ago

aliabd 6y ago
Would love some feedback! What additional interfaces or functionality would you like to see here?
- sirpunch 6y ago
  Excellent work, OP! It'd be great to have one setup for gpt-n demos. Something like a textfield where user types a prompt and a sidebar where sentence suggestions are populated every time users presses tab key. A suggested sentence could be inserted into the textfield by clicking on it in the sidebar.
  - aliabd 6y ago
    Thanks! That's a great idea, fyi we have a gpt-2 colab demo up, but the interface could be better I agree https://colab.research.google.com/drive/1o_-QIR8yVphfnbNZGYemyEr111CHHxSv?usp=sharing https://colab.research.google.com/drive/1o_-QIR8yVphfnbNZGYe...
- pchal 6y ago
  What about supporting tabular datasets?
  - aliabd 6y ago
    That's on our pipeline! Right now we support sliders, but we'll be handling csv data soon.
beagle3 6y ago
ML in this case = Machine Learning (not the programming language family that includes SML, MLton and OCaml)
- aliabd 6y ago
  Yes, good point. :)
- shpongled 6y ago
  I was just digging around earlier today trying to find if an SML language server exists (sadly, the answer is no), and this title got my hopes up just a little bit
cschneid 6y ago
This is cool, I am playing around with ML myself, and was just looking for a lightweight way to get dynamic input to models. The minst handwriting demo in the readme is almost exactly what I wanted. I have no idea what the architecture is, but it would be really cool to have this dynamic interface play nice with VSCode's notebook (jupyter) functionality, so I can add dynamic inputs right inline with the rest of the code.
- aliabd 6y ago
  Thanks! We render inline on jupyter/colab. I'm not sure about VSCode, but it boils down to whether it can render iframe or not. Try saving one of the colabs (as a .ipynb) from https://gradio.app/ml_examples https://gradio.app/ml_examples and passing inline=True to launch()? I can also try it and let you know :)
- aliabd 6y ago
  Update: it works! Check it out here: https://imgur.com/zPZdvlK https://imgur.com/zPZdvlK Let me know if this is what you meant :)
  - cschneid 6y ago
    Wow, very cool. That's exactly what I was thinking.
cdipaolo 6y ago
Okay: 1. This is awesome. Seriously, I will use this the next time I'm prototyping an image or text model. 2. Is there a way to entirely disable telemetry? I could imagine wanting to use this for models within a company that use sensitive data, etc., but wouldn't want to or be able to use it if the model interface was published either to gradio's internal APIs or to some sharable link that wasn't on a corporate network.
- aliabd 6y ago
  1. Thanks, would love to see what you build :) 2. By default, we only create a localhost link, no share link is created (with the exception of colab as we cannot access localhost there). You can then use that to set up port forwarding etc. Let me know if this answers your question?
  - cdipaolo 6y ago
    I think you did answer my question for (2), thanks! I just got a bit scared by a link saying gradio.app in it.
    - aliabd 6y ago
      Makes sense :)
scribu 6y ago
It's cool that you can immediately update the output whenever the input changes. But what if the code inside the function changes? Do you have hot reloading functionality? Streamlit handles this by re-executing the whole script when detecting any code changes. You can cache certain resources (such as the model), but it's fiddly to get right.
- aliabd 6y ago
  We don't have hot reloading. We avoided caching certain resources because of this exact reason, its a bit finicky. But we're working on a better way to do it.
solidasparagus 6y ago
How does gradio differ from streamlit[1]? [1]https://github.com/streamlit/streamlit https://github.com/streamlit/streamlit
- aliabd 6y ago
  Streamlit is a great library, especially for creating full, standalone dashboards. Here's where I think Gradio's focus is different: - Our UI components are optimized for machine learning models. For example, we make it super easy for you to put in a drag-and-drop image upload for your image classification model, and we'll handle the preprocessing to convert the input image to a numpy array of specified shape & the postprocessing to convert the confidences to nice graphical labels. We're trying to eliminate boilerplate preprocessing & postprocessing as much as possible. Just specify the UI components that make sense for your model in 1 line of code, and then launch() to create the interface! - We are designing our UI components so that you can get more insight into how your model is performing. For example, here we obscure / crop different parts of an image to explore what in the image might be causing the model to predict a cheetah: https://i.imgur.com/t0Inliy.mp4 https://i.imgur.com/t0Inliy.mp4 We are planning on releasing a lot more features specifically focused on model testing & validation, and would love to hear from you if that sounds useful - Gradio integrates seamlessly with jupyter / colab notebooks, so you can use your existing workflow (I don't believe that's true for streamlit)
nl 6y ago
Just noting that your MNIST demo on https://www.gradio.app/ https://www.gradio.app/ seems to have a bug. If you create a small zero it is classified as a 9. Or perhaps it is overly sensitive to line width? Drawing large circles counterclockwise with the small pen seems to be misclassified too.
- alibero 6y ago
  Yeah, the MNIST model seems to have issues. I can get it to make mistakes for all line widths and most digits. Maybe the issue with small digits is that there is no cropping happening and the model was trained on MNIST where all the digits are uniform size. Actually this is probably a good demo for a ML visualization tool as we were pretty easily able to find these issues. If cropping is the issue, this is also something that a test set might not catch.
  - aliabd 6y ago
    Yup that's a great point! So cool to see the model begin to break with crowd testing
- aliabd 6y ago
  Yes we're updating this model, you're right its pretty bad...
antman 6y ago
This looks great, another competitor is streamlit. You guys need a data grid. Most the Internet tutorials, research successes in Deep Learning are in NLP and Computer Vision. But most of the times in an actual setting people will also use a data grid to show results and/or input data.
- aliabd 6y ago
  That's a really great point, we're working on getting a tabular interface up (something like a csv input)
  - antman 6y ago
    Don’t know if it’s relevant but optional interface to use also existing Jupyter components e.g. qgrid could be a quick workaround to introduce features until native components are developed

85 points by aliabd 6y ago

aliabd 6y ago

Would love some feedback! What additional interfaces or functionality would you like to see here?

sirpunch 6y ago
Excellent work, OP! It'd be great to have one setup for gpt-n demos. Something like a textfield where user types a prompt and a sidebar where sentence suggestions are populated every time users presses tab key. A suggested sentence could be inserted into the textfield by clicking on it in the sidebar.
- aliabd 6y ago
  Thanks! That's a great idea, fyi we have a gpt-2 colab demo up, but the interface could be better I agree https://colab.research.google.com/drive/1o_-QIR8yVphfnbNZGYemyEr111CHHxSv?usp=sharing https://colab.research.google.com/drive/1o_-QIR8yVphfnbNZGYe...
pchal 6y ago
What about supporting tabular datasets?
- aliabd 6y ago
  That's on our pipeline! Right now we support sliders, but we'll be handling csv data soon.

beagle3 6y ago

ML in this case = Machine Learning (not the programming language family that includes SML, MLton and OCaml)

aliabd 6y ago
Yes, good point. :)
shpongled 6y ago
I was just digging around earlier today trying to find if an SML language server exists (sadly, the answer is no), and this title got my hopes up just a little bit

cschneid 6y ago

This is cool, I am playing around with ML myself, and was just looking for a lightweight way to get dynamic input to models. The minst handwriting demo in the readme is almost exactly what I wanted. I have no idea what the architecture is, but it would be really cool to have this dynamic interface play nice with VSCode's notebook (jupyter) functionality, so I can add dynamic inputs right inline with the rest of the code.

aliabd 6y ago
Thanks! We render inline on jupyter/colab. I'm not sure about VSCode, but it boils down to whether it can render iframe or not. Try saving one of the colabs (as a .ipynb) from https://gradio.app/ml_examples https://gradio.app/ml_examples and passing inline=True to launch()? I can also try it and let you know :)
aliabd 6y ago
Update: it works! Check it out here: https://imgur.com/zPZdvlK https://imgur.com/zPZdvlK Let me know if this is what you meant :)
- cschneid 6y ago
  Wow, very cool. That's exactly what I was thinking.

cdipaolo 6y ago

Okay: 1. This is awesome. Seriously, I will use this the next time I'm prototyping an image or text model. 2. Is there a way to entirely disable telemetry? I could imagine wanting to use this for models within a company that use sensitive data, etc., but wouldn't want to or be able to use it if the model interface was published either to gradio's internal APIs or to some sharable link that wasn't on a corporate network.

aliabd 6y ago
1. Thanks, would love to see what you build :) 2. By default, we only create a localhost link, no share link is created (with the exception of colab as we cannot access localhost there). You can then use that to set up port forwarding etc. Let me know if this answers your question?
- cdipaolo 6y ago
  I think you did answer my question for (2), thanks! I just got a bit scared by a link saying gradio.app in it.
  - aliabd 6y ago
    Makes sense :)

scribu 6y ago

It's cool that you can immediately update the output whenever the input changes. But what if the code inside the function changes? Do you have hot reloading functionality? Streamlit handles this by re-executing the whole script when detecting any code changes. You can cache certain resources (such as the model), but it's fiddly to get right.

aliabd 6y ago
We don't have hot reloading. We avoided caching certain resources because of this exact reason, its a bit finicky. But we're working on a better way to do it.

solidasparagus 6y ago

How does gradio differ from streamlit[1]? [1]https://github.com/streamlit/streamlit https://github.com/streamlit/streamlit

aliabd 6y ago
Streamlit is a great library, especially for creating full, standalone dashboards. Here's where I think Gradio's focus is different: - Our UI components are optimized for machine learning models. For example, we make it super easy for you to put in a drag-and-drop image upload for your image classification model, and we'll handle the preprocessing to convert the input image to a numpy array of specified shape & the postprocessing to convert the confidences to nice graphical labels. We're trying to eliminate boilerplate preprocessing & postprocessing as much as possible. Just specify the UI components that make sense for your model in 1 line of code, and then launch() to create the interface! - We are designing our UI components so that you can get more insight into how your model is performing. For example, here we obscure / crop different parts of an image to explore what in the image might be causing the model to predict a cheetah: https://i.imgur.com/t0Inliy.mp4 https://i.imgur.com/t0Inliy.mp4 We are planning on releasing a lot more features specifically focused on model testing & validation, and would love to hear from you if that sounds useful - Gradio integrates seamlessly with jupyter / colab notebooks, so you can use your existing workflow (I don't believe that's true for streamlit)

nl 6y ago

Just noting that your MNIST demo on https://www.gradio.app/ https://www.gradio.app/ seems to have a bug. If you create a small zero it is classified as a 9. Or perhaps it is overly sensitive to line width? Drawing large circles counterclockwise with the small pen seems to be misclassified too.

alibero 6y ago
Yeah, the MNIST model seems to have issues. I can get it to make mistakes for all line widths and most digits. Maybe the issue with small digits is that there is no cropping happening and the model was trained on MNIST where all the digits are uniform size. Actually this is probably a good demo for a ML visualization tool as we were pretty easily able to find these issues. If cropping is the issue, this is also something that a test set might not catch.
- aliabd 6y ago
  Yup that's a great point! So cool to see the model begin to break with crowd testing
aliabd 6y ago
Yes we're updating this model, you're right its pretty bad...

antman 6y ago

This looks great, another competitor is streamlit. You guys need a data grid. Most the Internet tutorials, research successes in Deep Learning are in NLP and Computer Vision. But most of the times in an actual setting people will also use a data grid to show results and/or input data.

aliabd 6y ago
That's a really great point, we're working on getting a tabular interface up (something like a csv input)
- antman 6y ago
  Don’t know if it’s relevant but optional interface to use also existing Jupyter components e.g. qgrid could be a quick workaround to introduce features until native components are developed