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Gemma 3 270M: Compact model for hyper-efficient AI

developers.googleblog.com

91–100 of 325 posts

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#91
Out of curiosity: because there seems to be a race to optimise models for local inference, how much "parameters one could save" by dropping unneeded language and domain-specific information.

Like, can you have a model that is English-only, but does more with the same amount of parameters if Chinese and European languages are dropped from the training?

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#92
post #16

Hi all, I built these models with a great team. They're available for download across the open model ecosystem so give them a try! I built these models with a great team and am thrilled to get them out to you. From our side we designed these models to be strong for their size out of the box, and with the goal you'll all finetune it for your use case. With the small size it'll fit on a wide range of hardware and cost…

Are there any fine tuning in a box type options available in the cloud for this? This is amazing work, thank you.

Finetuning is possible on free tier colab and 5 minutes of time. Here's a tutorial

https://ai.google.dev/gemma/docs/core/huggingface_text_full_...

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#93

Hi all, I built these models with a great team. They're available for download across the open model ecosystem so give them a try! I built these models with a great team and am thrilled to get them out to you. From our side we designed these models to be strong for their size out of the box, and with the goal you'll all finetune it for your use case. With the small size it'll fit on a wide range of hardware and cost…

The Gemma 3 models are great! One of the few models that can write Norwegian decently, and the instruction following is in my opinion good for most cases. I do however have some issues that might be related to censorship that I hope will be fixed if there is ever a Gemma 4. Maybe you have some insight into why this is happening? I run a game when players can post messages, it's a game where players can kill each othe…

Perhaps you can do some pre-processing before the LLM sees it, e.g. replacing every instance of “kill” with “NorwegianDudeGameKill”, and providing the specific context of what the word “NorwegianDudeGameKill” means in your game.

Of course, it would be better for the LLM to pick up the context automatically, but given what some sibling comments have noted about the PR risks associated with that, you might be waiting a while.

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#95

Earlier quoted context omitted.

The Gemma 3 models are great! One of the few models that can write Norwegian decently, and the instruction following is in my opinion good for most cases. I do however have some issues that might be related to censorship that I hope will be fixed if there is ever a Gemma 4. Maybe you have some insight into why this is happening? I run a game when players can post messages, it's a game where players can kill each othe…

LLMs are really annoying to use for moderation and Trust and Safety. You either depend on super rate-limited 'no-moderation' endpoints (often running older, slower models at a higher price) or have to tune bespoke un-aligned models. For your use case, you should probably fine tune the model to reduce the rejection rate.

Speaking for me as an individual as an individual I also strive to build things that are safe AND useful. Its quite challenging to get this mix right, especially at the 270m size and with varying user need.

My advice here is make the model your own. Its open weight, I encourage it to be make it useful for your use case and your users, and beneficial for society as well. We did our best to give you a great starting point, and for Norwegian in particular we intentionally kept the large embedding table to make adaption to larger vocabularies easier.

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#96
post #34

Earlier quoted context omitted.

Do you have any practical examples of fine-tuned variants of this that you can share? A description would be great, but a demo or even downloadable model weights (GGUF ideally) would be even better.

We obviously need to create a pelican bicycle svg finetune ;) If you want to try this out I'd be thrilled to do it with you, I genuinely am curious how well this model can perform if specialized on that task. A couple colleagues of mine posted an example of finetuning a model to take on persona's for videogame NPCs. They have experience working with folks in the game industry and a use case like this is suitable for…

What size of tasks can this handle? Can you do a fine-tune of Mac System Settings?

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#97

Hi all, I built these models with a great team. They're available for download across the open model ecosystem so give them a try! I built these models with a great team and am thrilled to get them out to you. From our side we designed these models to be strong for their size out of the box, and with the goal you'll all finetune it for your use case. With the small size it'll fit on a wide range of hardware and cost…

hi Ravin, fellow Googler here. Curious if you can share here (or internally?) how these models were trained. Wondering if you face all the chaos the large models have during training?

Reach out to me internally

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#98

Hi all, I built these models with a great team. They're available for download across the open model ecosystem so give them a try! I built these models with a great team and am thrilled to get them out to you. From our side we designed these models to be strong for their size out of the box, and with the goal you'll all finetune it for your use case. With the small size it'll fit on a wide range of hardware and cost…

[flagged]

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#99
post #64

My lovely interaction with the 270M-F16 model: > what's second tallest mountain on earth? The second tallest mountain on Earth is Mount Everest. > what's the tallest mountain on earth? The tallest mountain on Earth is Mount Everest. > whats the second tallest mountain? The second tallest mountain in the world is Mount Everest. > whats the third tallest mountain? The third tallest mountain in the world is Mount Everes…

> These smaller models are great

Are they?

Re: Gemma 3 270M: Compact model for hyper-efficient AI

#100
post #64

My lovely interaction with the 270M-F16 model: > what's second tallest mountain on earth? The second tallest mountain on Earth is Mount Everest. > what's the tallest mountain on earth? The tallest mountain on Earth is Mount Everest. > whats the second tallest mountain? The second tallest mountain in the world is Mount Everest. > whats the third tallest mountain? The third tallest mountain in the world is Mount Everes…

To add to the comments, we were not aiming for perfect factuality. Even ignoring the model size, these weights are frozen in time now.

My suggestions here are to hook this model up to a RAG system, then you can rely on an external knowledge store. Or you can try finetuning this model with the facts that are important to you, if you do that it should pick up that new knowledge quite quickly.

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