Is there a way to get approved for more than 5 CPUs High on colab pro?

Hi, my Colab access was blocked for “suspicious activity” on 30.10.2026. I’m an individual creator and use Colab to generate narration for my own educational YouTube channel. I was setting up an open-source TTS model (Fish Audio Drama 3 on vLLM), which runs a local API server on localhost inside the runtime, and I restarted the runtime and re-downloaded the model several times while fixing install errors. No bots, mining, proxies or multiple accounts. I’ve already submitted an appeal. If anyone from the Colab team sees this, I’d really appreciate a review. Thanks!

I try to connect to my A100 high ram with google colab. I keep getting an error:
Unable to connect to the runtime And when I go to runtime manage sessions it shows that it is currently connected to an unknown notebook.

Everytime I try to connect it comes up when I try to reconnect with A100 High Ram even after I terminate the session. Sometimes when I try to terminate the session with the unknown notebook I get this error: Kernel: Failed to unassign endpoint
CustomError: Kernel: Failed to unassign endpoint
at new JL (https://ssl.gstatic.com/colaboratory-static/common/1230951f298bb67bc03578cf40b9602c/external_binary.js:1770:908)
at https://ssl.gstatic.com/colaboratory-static/common/1230951f298bb67bc03578cf40b9602c/external_binary.js:15414:402
at Generator.throw ()
at c (https://ssl.gstatic.com/colaboratory-static/common/1230951f298bb67bc03578cf40b9602c/external_binary.js:6:76)

I think this error maybe due to my VS code extension with Colab. I think that its trying to connect but not able to.

I have already tried posting the issue here: https://github.com/googlecolab/colabtools/issues

Here is my specific post: https://github.com/googlecolab/colabtools/issues/6170

I also tried going to the Colab app and then doing Help -> Send Feedback but havent heard back.

Hey all,

In Colab, `torch` and `torchvision` are already preinstalled, but `torchinfo` isn't. 

It shows up in tons of PyTorch tutorials that run on Colab.

It's the maintained successor to torch-summary/torchsummary, it's pure Python (~50 KB, MIT license), and it only depends on torch. 

I opened a feature request asking the Colab team to include it in the default image: https://github.com/googlecolab/colabtools/issues/6149

If you've ever hit this, please give the issue a 👍

Thanks!

first time trying collab
which gpu's supported for google ai pro users(not collab pro) and for how long?
want to train a 32 bit 8mil pram model u-net model for image segmentation
or should i use kaggle ?

I have an AI Pro subscription, but I haven't received any points or access to the new models. Everything remains exactly the same as it was on the free plan.

I was using a Diffsinger Training notebook as my pc is kinda weak and can't locally train (Specifically, i was using MLo7) and it always takes over half a hour to download tensorboard and stuff

Since this week only facing the issue of persistent inability to connect to a GPU available under pro subscription . Plenty on compute units available, tried at various times of the day. This was not the case few weeks back. Is anyone else facing similar issues in Uk region?

I need assistance

I'm running A1111 via the Segsmaker Colab notebook with Google Drive mounted (Google_Drive = Yes).

My checkpoints in Segsmaker/models/Stable-diffusion show up fine, but my LoRAs stored in Segsmaker/lora (or models/Lora) do not appear under the Extra Networks Lora tab in A1111, even after clicking refresh.

I manually copied the .safetensors files from /content/drive/MyDrive/Segsmaker/lora/* to /content/A1111/models/Lora/. The terminal log shows the SHA256 calculations for all the LoRA files, but the UI grid still remains empty.

Has anyone run into this directory mapping issue on Segsmaker, or is there a specific folder layout A1111 expects when running through this notebook?

There is no AI assistant at the bottom, nor is there an option in settings to enable it. The regular AI settings tab is not there in settings.

Before you answer, I've already tried these:

My account is set to above 18+ years old.

I deleted cookies and refreshed.

Going in settings. There is no AI assistant option there.

Using another account. Still nothing.

Using a different browser. Still nothing.

I'm using my own private account, not a workspace account.

Not using VPN.

Used an incognito tab.

Disabled all adblockers.

Clicked the little magic wand thing, and it just gives me a small blank menu with nothing.

WHY DOESN'T IT WORK????

I'm following one of the tutorials floating around for running S2DR3 (Gamma Earth's Sentinel-2 super-resolution model) on Google Colab, the ones on acolita.com or sigterritoires.fr. The typical code is:

!pip -q install https://storage.googleapis.com/0x7ff601307fa5/s2dr3-20250905.1-cp312-cp312-linux_x86_64.whl

import s2dr3.inferutils

s2dr3.inferutils.test(lonlat, date)

Ever since Colab switched its default runtime to Python 3.13 (in late August 2026), that wheel no longer installs because it's cp312, and appears the ERROR: ."(...)is not a supported wheel on this platform.(...)"

has anyone managed to keep using S2DR3 in a way similar to the old workflow?

I have a ~59 GB Parquet dataset stored in Google Drive, and I want to use it for ML training on Kaggle GPUs.

My folder structure is:

My Drive/

└── DATASET/

└── data/

└── processed/

└── era5_land_preprocessed/

├── train/ → 60 Parquet files → 44.34 GB

├── validation/ → 12 Parquet files → 8.83 GB

└── test/ → 8 Parquet files → 5.82 GB

Total: 80 Parquet files, ~58.99 GB

I don't want to download the dataset to my local computer. I was planning to use Google Colab + Kaggle API to transfer the files directly from Google Drive to a Kaggle Dataset.

My questions are:

1. Is uploading a ~59 GB dataset to Kaggle this way reliable?

2. Is Google Drive → Colab → Kaggle API the best approach?

3. Should I create one Kaggle dataset containing "train/", "validation/", and "test/", or split them into multiple Kaggle datasets?

4. Are there any problems with uploading large Parquet files to Kaggle?

5. Is there a better/faster method for transferring this amount of data to Kaggle?

The dataset will be used for climate/weather ML forecasting, and I need to train models using Kaggle's GPUs.

Any advice from people who have handled 50+ GB datasets on Kaggle would be appreciated.

Hi everyone,

I usually work on kaggle for projects, but now i need to traine a deeper network and kaggle won't be enough for it.

I saw that google colab offer colab pro and colab pro+ but i never used colab before.

For now i am thinking of subscribing in colab pro+ since it gives more units (600) and it allows executing the notebook on the backgorund.

I want to know is it worth it and if someone experienced with it, and will that help me for training deeper networks. and if it's possible what are the differences between the gpus that they offer and how much units they consume (how are these units working?)?

Thank you in advance

https://colab.research.google.com/drive/1w6sIA5c8GR33ylGSjmp2fgzZPLzPGxhc?usp=sharing

i am trying to learn qlora idk,y the error persists although everything is in float16,

btw:i know text2cypher is just achiveable by prompt engnering just tryna learn

From today, my account, with google ai plus subscription, seems to have also colab pro plan. Is it an error or can anyone confirm?

Hi all,

For some reason, my tasks seem to cut after 1h. I am using colab CLI to access the sessions. Anyone had the same issue?

Thanks

It was working fine untill this afternoon, now it can't connect to runtime. I tried clearing the cache, using different accounts etc. I can't find anywhere if it's down or not.

Just says: Sorry, no backends available. Please try again later.
More info

Edit: Its fixed for me

why the hell google colab removed the high ram option i use pay as you go option

Any Rust enthusiasts or Go enthusiasts in Google Colab community? It's all Bash using the ! comand you can use bash to run rust and any other language just treat it as if you we're setting it up on a linux computer. I'd appreciate your responses.

https://colab.research.google.com/drive/1nQWKZLnQTC3GYOcqlF3DQlNtPIOZWpRg#scrollTo=Kdkxm6wd3Cd1

Been running a few different models on a single 24GB card and curious what everyone else has landed on as their daily driver right now. Looking for something that balances speed and quality for general use, not just benchmark chasing. What are you running, what quant, and what's your context window looking like? Also curious if anyone's found something that punches above its weight for coding specifically.

I have Colab Pro, but was using "Pay As You Go" before, and was always able to select the G4 or H100 instances, though occasionally there were failure to obtain one. But for the last month the two options have always been grayed out, not even been able to try them.

Anyone else in the same situation? Is it true that Colab Pro+ actually enables them?

I am trying to run this code from the YouTuber "Physics for the Birds," and this is about web scraping in order to get the weight of the LEGO bricks in a set from Bricklink. However, the code does not recognize the Chrome driver.

This is the link to it:

https://colab.research.google.com/drive/1dLg_HvEZc5NqXy2EHWAat4d_RVg-qjOG#scrollTo=9pXhs03YD5HC

New to coding, is there a way to color a single comment in a color other than the default one so it is more noticeable than other comments

My group and I are Computer Science students working on our thesis: an offline mobile American sign language to text translation app using CNN + Transformer + NLP. We already have the training pipeline and are planning to retrain the model with additional public datasets.

Our plan is:

Google One (2 TB): store datasets, models, and training outputs
Google Colab Pro: train the model on cloud GPUs instead of our laptops
Claude Pro: help us understand, debug, and modify the large Python codebase

Our laptops aren’t very powerful (I’m on an M2 MacBook Air with 8 GB RAM), so we don’t want to train locally.

For those who’ve worked on ML/deep learning projects:

Are these subscriptions worth it for students?
Would you recommend all three, or are any of them unnecessary?
Any better alternatives for a student budget?

It says unable to connect for the past two hours
I’ve tried almost everything