canyon289

7 ms·

61.
by canyon289 1y ago
This would be a great experiment. I'm not sure how the OS integration would work, but as a first pass you could try finetuning the model to take natural language "my colors on the screen look to dark" and then have it output
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by canyon289 1y ago
Any text to text use case with 32k context, especially if you're starting from the PT version you can finetune it to do whatever you need
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by canyon289 1y ago
32k context window so whatever fits in there. What is a finetune of mac system settings?
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by canyon289 1y ago
Because there is a simultaneous need out of the box generalized models. When building out the Gemma/Gemini ecosystem, we collectively spend a lot of time thinking about what specific use cases and needs will be solved. To this point on
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by canyon289 1y ago
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
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by canyon289 1y ago
Reach out to me internally
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by canyon289 1y ago
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
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by canyon289 1y ago
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_...
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by canyon289 1y ago
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 min
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by canyon289 1y ago
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.
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by canyon289 1y ago
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
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by canyon289 1y ago
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
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by canyon289 1y ago
Im a research person building models so I can't answer your questions well (save for one part) That is, as a research person using our GPUs and TPUs I see first hand how choices from the high level python level, through Jax, down to th
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by canyon289 1y ago
I work at Google on these systems everyday (caveat this is my own words not my employers)). So I simultaneously can tell you that its smart people really thinking about every facet of the problem, and I can't tell you much more than th
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by canyon289 2y ago
Ah this is different. The Nytimes article is about identifying/classifying dolphins from audio. This new model is about communicating with dolphins from generated audio. The difference between recognizing someone from hearing them, and
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by canyon289 2y ago
I work at Google on the Gemma team, and while not on the core team for this model, participated a bit on this project. I personally was happy to see this project get built. The dolphin researchers have been doing great science for years, fr
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by canyon289 2y ago
Of course! Glad you can find models that work well for you and we're all learning together. Even on the "expert side" we're learning from what folks like yourself are doing and taking note so we can shape these models to
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by canyon289 2y ago
Ah, There's a distinction here with model vs model framework. The ollama inference framework supports token output restriction. Gemma in AI Studio also does, as does Gemini, there's a toggle in the right hand panel, but that'
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by canyon289 2y ago
With open models this isn't as true. The weights are local, you bring your own compute, there's nothing between you and the model. Regarding what is a better result, personally I encourage you to define what a better result is in
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by canyon289 2y ago
Ah I see where confusion might come. I don't mean the exact prompt shouldn't matter, but I am saying that we noticed that these series of models picked up on tool call format quite readily in our various tests, which is what we ex
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by canyon289 2y ago
This is me speculating along with you so don't take this as fact, but my sense is that the LLMs tool stack is getting "layerized" like network layer architectures. Right now the space is moving fast so new concepts and things
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by canyon289 2y ago
Thank you! Community vibes motivate us to code more up for you all. Really appreciate the note. Regarding the device theme in the browser, I'll ask some folks what's going on there.
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by canyon289 2y ago
We feel this model excels at instructability which is why we're recommending bringing your own prompt! Benchmark wise you can see this performance from BFCL directly, they (independently) ran their eval using their prompted format the
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by canyon289 2y ago
So in short there's no guarantee for any output from any LLM whether its Gemma or any other (ignoring some details like setting a random seed or parameters like temperature to 0). Like you mentioned though libraries like outlines can c
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Gemma3 Function Calling(ai.google.dev)
202 points by canyon289 2y ago|32 comments
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by canyon289 2y ago
Hey folks, I'm on the Gemma team, we released new model(s) just recently, and I saw many questions here about function calling. We just published the docs to detail this more. In short Gemma3's prompted instruction following is qu
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by canyon289 2y ago
Hey, I'm from the Gemma team. There's a couple of angles to your question We do care about prompted instructions, like json schema, and it is something we eval for and encourage you to try. Here's an example from Gemma2 to gu
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by canyon289 2y ago
Hey, I'm Ravin from the Gemma team. It's on ollama! Try `ollama run gemma3` to get it pulled locally
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by canyon289 2y ago
I wrote a couple of these books (and published them as open access) Here's my one on computation probability. The code and math here underlie "AI". It's the same fundamentals, and even code libraries (Jax, pytorch etc(
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by canyon289 2y ago
I work on frontier models directly and I I wrote a guidebook for folks like you. https://ravinkumar.com/GenAiGuidebook/book_intro.html It has a mix of concepts and hands on code, and lots of links to the best places to

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