Each time I tried to open a new notebook in the Chrome browser it failed.
Then I tried to open a new notebook in the Firefox browser and it worked. I was then able to open a copy of the notebook you provided (I modified the permissions of the copy), run lesson1 and save it.
Now to use the chrome browser. I clicked the upper right menu icon then selected New incognito window and was able to open a new notebook in the Chrome browser, then I select Open Drive notebook.
I can run Lesson #1 on Crestle with no problem but when I run the same notebook on Google Colab after installing the relevant libraries and downloading the relevant data I get this error message. As a temporary workaround I made the following revision and now the script runs until the end:
My question is if anybody here happens to have a version of Lesson #1 that is able to run in full on Google Colab at the time of this posting? Did you have to make a similar modification to the code? If so, I would appreciate if you could share your entire .ipynb file so that I can compare my solution (see github link) to yours.
I had done so but it isnât with the latest fast.ai version per se (itâs equivalent to 5 Months old fast.ai but its working seamless just as Jeremy has shown as)
And itâs not at all slowâŠ
Actually itâs faster than AWS actuallyâŠ(might be lucky)
Thank you for sharing your .ipynb file @ecdrid. I get a different error with your notebook as compared to my notebook, however. Maybe there are compatibility issues between fastAI and Google Colab? The unmodified Lesson #1 notebook runs fine on Crestle, thankfully.
@ecdrid, in your file there was an error after the very first learn.fit and later on there are PIL library errors and CUDA memory errors too. Are you able to run the script without any errors? Does anyone else have a .ipynb file that can run Lesson #1 on Google Colab without using the temporary workaround that I mentioned in my initial post?
Hi
I have faced this error during running the first model quick start section:
Failed to display Jupyter Widget of type HBox.
If youâre reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean that the widgets JavaScript is still loading. If this message persists, it likely means that the widgets JavaScript library is either not installed or not enabled. See the Jupyter Widgets Documentation for setup instructions.
If youâre reading this message in another frontend (for example, a static rendering on GitHub or NBViewer), it may mean that your frontend doesnât currently support widgets.
I want to train upload my data into my current notebook. I tried putting it on filehosting sites and then tried downloading it viawget https://dl.dropboxusercontent.com/content_link/GjAxYko7UsfBU2Iio68DZ15qAOsWzVb20sKDyUh1yFfGFvQ1tR3EJeXfb2zio7Ia/file?dl=1 && unzip blackswhites.zip -d data
This doesnât work. How can i get the data into my current environment?
Ideally Iâd like to directory transfer data from Kaggle to Colab, without going through my machine, as the uplink on my home internet is very slow and the files are taking long time to get to Colab.
Actually I found a solution to Kaggle -> Colab direct transfer.
I used the CurlWget extension Jeremy describes here [https://youtu.be/9C06ZPF8Uuc?t=744] and then invoke !wget ... from Colab to download into my Google Drive. Extremely fast transfer all within Google Cloud.
There is the API key to Kaggle which makes the access straightforward, as if you were on Kaggle Kernels:
install Kaggle API: !pip install kaggle
API Credentials
To use the Kaggle API, go to the âAccountâ tab of your user profile (https://www.kaggle.com//account) and select âCreate API Tokenâ. This will trigger the download of kaggle.json, a file containing your API credentials.
Place this file on your Google Drive anywhere.
With the next snippet you download your credentials to Colab and you can start using Kaggle API: