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

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

#81
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…

It's an instruction following model, not a micro-wikipedia. It's not meant to answer factual questions nor even be general purpose. It's meant to follow instructions and be easy to fine-tune for your own specific use case.

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

#83

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…

Amazing work. This model feels really good at one-off tasks like summarization and autocomplete. I really love that you released a quantized aware training version on launch day as well, making it even smaller!

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

#84
post #37

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…

Very cool. For the INT4 QAT model, what is the recommended precision for the activations and for the key and values stored in KV cache?

For keys, you probably want to use at least q5 or q6, for values q4 is fine

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

#85
post #83

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…

Amazing work. This model feels really good at one-off tasks like summarization and autocomplete. I really love that you released a quantized aware training version on launch day as well, making it even smaller!

Thank you Jeffrey, and we're thrilled that you folks at Ollama partner with us and the open model ecosystem.

I personally was so excited to run ollama pull gemma3:270b on my personal laptop just a couple of hours ago to get this model on my devices as well!

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

#86

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…

You reminded me of an awesome Google engineer I met at BSidesSF last year who tirelessly answered my questions, and when I clicked on the video, it was you! That was a really inspiring moment for me, thank you.

BSidesSF is a fantastic event, glad you're able to attend. There's some great people organize it and if you want to help out they're always looking for volunteers. Happy to make an intro if you like.

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

#87
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…

You are testing this model for knowledge. That's not the primary use of a model like this. They are meant for instilling domain specific skills and knowledge through fine-tuning. The blog post goes into that a lot. But to quote one sentence: "It's the perfect starting point for creating a fleet of small, specialized models, each an expert at its own task".

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

#88

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…

What effort do you folks take to see your models actually running on hardware such as AMD Strix Halo or Apple M3M4? I get the sense that AI is at the “hobby kit computing” stage where they used to dump all the components in a box and give you a schematic and a soldering iron and happily say “you make it work!” And that worked in the early days of computing because there was a small number of people really motivated f…

Here you go, one click installer - https://lmstudio.ai

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

#89
post #34

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…

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 game devs who want to start including lightweight models that won't take up a ton of accelerator memory and can run efficiently on CPU if needed. https://ai.google.dev/gemma/docs/core/huggingface_text_full_...

As for GGUF it's available here! https://huggingface.co/collections/ggml-org/gemma-3-270m-689...

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