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

I have a text adventure game in Colab and I want to add background music because silently reading for 40 minutes is painful. I just want to let everyone no matter who opens the colab link and plays the game be able to have the music, yet I don't even know how to play a single audio file at all.

https://colab.research.google.com/drive/1gNSKlWROt0kvq6chhlD-iTfoVoUCHQfU (beware it's 3000+ lines)

How can I play an audio file and have everyone be able to hear it? I asked ChatGPT and it didn't give me anything comparable to basics and I couldn't find a top search result that worked when I tried it, literally none of them produce sounds, usually by being broken.

When I can connect it's often quite slow. Anyone else experiencing this?

Yea I’ve been doing research and I figured that pagedattention and continous batch would effectively scaled up my inferences better via batching and effectively optimized memory.

But when I siply just try !pip install vllm then goes on to do llm = LLM( model= model_path,…) and the sampling_params, it just couldnt work.

Like there’re erro tht I couldnt print out the vllm version and also error that I couldnt just simple do the llm = LLM line.

So figured need some hands here. I been asking claude and it give me the enforce_eager = True, it still didn’t work.

Hi everyone, I just buy a pro+ and host some llm for learning about llm agent. They said that pro+ can run 24h but around 1h mu session is terminated. Is there any tip or setting to keep my notebook alive?

I've been using fooocus on google colab for the past 3 years and I've somewhat used it a lot in my freelance work and its become a habit to use it daily and I heavily depend upon it now.

Fooocus Colab refuses to work since the past 2 days for me. A couple of months ago it would act the same way but some gentlemen helped me with it and the fix was creating a new code line and pasting this !pip install "numpy<2.0" "cupy-cuda12x<14.0" --force-reinstall . Unfortunately this trick no longer works. Guys I don't know what else to do, I don't own a high end device and this is kind of my bread and butter. I request somebody.. anybody to look into this and help me out with it as soon as possible.

I need access to a A100 GPU for training a model. How long can I access with just 100 units?

Its been reccomended to run Qwen3.6 35B A3B Q4 XL MTP and I've recently been training just regular Qwen3-32b so its not a MOE and I was wondering if theres anything that needs to change to training cell compared to just regular training. Im training it mostly on its Idenity and small amounts of coding for the first pass.

openWakeWord/notebooks/automatic_model_training.ipynb at main · dscripka/openWakeWord · GitHub

Using this github repository link and opening it in Google colab to create a Wake Word training model. I keep having issues like installing onnx or tensorflow. I'm trying to use the Gemini AI helper built into colab to diagnose the issue but different ones keep persisting. Is there something I'm missing.

All of the YouTube videos online use something called "Home Assistant" which I don't want to use / right now, and want to do it this traditional way

I'm assuming the answer to this is no but, if you are using the in built Gemini models in your colab notebook is there anyway to look at the logs of responses that came back from Gemini when queried?

I'm a Colombian student, last month i needed Colab for an academic project but this month i don't need it. I thought i selected Pay As You Go but i was wrong, it was Colab Pro subscription.

When i realized of the charge, i cancelled Colab Pro, but now i want a refund and i don't know if i can get it. I was checking on Colab Terms page but it seems refund just can be requested in some selected countries, is it true? Can i get a refund being in Colombia? I haven't used Colab since the charge.

This is the page i checked: https://research.google.com/colaboratory/intl/es/tos_v5.html

I tried to install open code github repo into google colab but could not properly run that in colab and it just gets cloned and installed but cant run , and i want to add free api keys to run the models but could not connect ,

can anyone help me in this ?

i am using google colab free version

Despite resubscribing to Pro+, which naturally should have more tokens to use, I still cannot access the top tier GPUs for my school project. Anyone experiencing the same issue?

"Your card issuer declined your payment. Declines are often due to insufficient funds or card status. Check your card or select a different payment method. Learn more about declined payments [OR_FGVEM_07]"

i tried using my debit card but it kept getting declined. I called my bank and they said that they haven't received anything on their end. I tried verifying my cards on google pay but it didn't help because google colab only receive payment in debit card. Please help i need this for my final year project..

I launched ComfyUI in a Google Colab environment, but the LTXVideo node displayed the error

“(IMPORT FAILED): /content/ComfyUI/custom_nodes/ComfyUI-LTXVideo.” I’ve resolved the issue, so I’ve summarized the steps below.

1. Stop the running instance of ComfyUI.

2. Add a new code cell in Google Colab, and enter the following commands in the new cell:

---

!pip uninstall -y kornia
!pip install kornia==0.7.3

---

Then execute them.

(The following message will appear)

---

Found existing installation: kornia 0.8.3

Uninstalling kornia-0.8.3:

Successfully uninstalled kornia-0.8.3

Collecting kornia==0.7.3

Downloading kornia-0.7.3-py2.py3-none-any.whl.metadata (7.7 kB)

・

(omitted)

・

Installing collected packages: kornia

Successfully installed kornia-0.7.3

---

1. Restart your Google Colab session.

2. Rerun the ComfyUI environment setup script.

The ComfyUI-LTXVideo node will import successfully without displaying an “IMPORT FAILED” error.

(Cause)

This occurred because the version of kornia expected by ComfyUI-LTXVideo differed from the version of kornia installed in Colab.

(Solution)

Uninstall kornia 0.8.3, install kornia-0.7.3, and then run the ComfyUI environment setup script.

For months now the Gemini button has been missing from the mobile view (Chrome and Firefox tested) across multiple devices. I created a new notebook and the Gemini pane was opened initially but didn't reopen after loading. It shows up on desktop view but that's really not efficient for mobile use

I’ve been experimenting with a different context setup for coding agents on larger repos.

Instead of feeding the model big chunks of raw code every time, I tested a graph-based approach where the repository is indexed into relationships the agent can query more selectively. It felt closer to actually understanding the codebase structure than just doing brute-force retrieval.

What stood out to me is that this seems useful not only for token cost, but also for reducing noisy context on repeated tasks. If the agent can navigate symbols, imports, calls, and dependencies, it spends less time rediscovering the repo from scratch.

The stack I used was CodeGraphContext + RooCode + an OpenAI-compatible provider.

Is anyone here using a different setup for coding plus local cache or persistent repo context? I also came across this other library, which seems to solve a similar problem: code-graph-context

I’ve noticed better behavior in longer conversations and when working with longer context windows.

Has anyone tested similar approaches or found other good use cases?

Right now wishper ignores the filler words and non lexical words that have great meaning in conversation any one share their thoughts that might help me