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Gemma 2: Improving Open Language Models at a Practical Size [pdf]

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Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#61
post #43

Earlier quoted context omitted.

Any gemma-2-9b or 27b 4 bit GGUF's on HuggingFace yet? Thanks!

If you are still looking for it, I just made it available on an app[1] that I am working on with Gemma2 support. https://msty.app

Are you saying you put a 4-bit GGUF on HuggingFace?

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#62

Are these small Gemma 2 distilled models available anywhere? I'm not finding them on huggingface.co, etc. but maybe I don't know the exact model names they are published. Are the weights released yet?

In addition to the HF links shared by sibling comments, the 2B will be released soon.

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#63

Hello (again) from the Gemma team! We are quite excited to push this release out and happy to answer any questions! Opinions are our own and not of Google DeepMind.

Given the goal of mitigating self-proliferation risks, have you observed a decrease in the model's ability to do things like help a user setup a local LLM with local or cloud software? How much is pre-training dataset changes, how much is tuning? How do you think about this problem, how do you solve it? Seems tricky to me.

[flagged]

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#64

Hello (again) from the Gemma team! We are quite excited to push this release out and happy to answer any questions! Opinions are our own and not of Google DeepMind.

The 4k sliding window context seems like a controversial choice after Mistral 7B mostly failed at showing any benefits from it. What was the rationale behind that instead of just going for full 8k or 16k?

This is mostly about inference speed, while maintaining long context performance.

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#65

Hello (again) from the Gemma team! We are quite excited to push this release out and happy to answer any questions! Opinions are our own and not of Google DeepMind.

It's fairly easy to pay OpenAI or Mistral money to use their API's. Figuring out how Google Cloud Vertex works and how it's billed is more complicated. Azure and AWS are similar in how complex they are to use for this. Could Google Cloud please provide an OpenAI compatible API and service? I know it's a different department. But it'd make using your models way easier. It often feels like Google Cloud has no UX or end…

Happy to pass on any feedback to our Google Cloud friends. :)

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#66
post #49
post #22

Earlier quoted context omitted.

Google is in a fight for their lives, I've fully moved over to paid services and haven't used google in about a month now.

If this were a common sentiment or rooted in reality I would imagine their stock would not be at an all time high...

I'm an early adopter. The rest of you will catch up in the next five years.

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#67
post #26

So it's twice the size of phi 3 and considerably worse? What am I missing

Worse in some aspects, better in other. Small models are never going to be generalists, so having several small models allows you to pick the one that best fits your needs.

When would you use which?

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#68

Hello (again) from the Gemma team! We are quite excited to push this release out and happy to answer any questions! Opinions are our own and not of Google DeepMind.

It's fairly easy to pay OpenAI or Mistral money to use their API's. Figuring out how Google Cloud Vertex works and how it's billed is more complicated. Azure and AWS are similar in how complex they are to use for this. Could Google Cloud please provide an OpenAI compatible API and service? I know it's a different department. But it'd make using your models way easier. It often feels like Google Cloud has no UX or end…

I plan on downloading a Q5 or Q6 version of the 27b for my 3090 once someone puts quants on HF, loading it in LM studio and starting the API server to call it from my scripts based on openai api. Hopefully it's better at code gen than llama 3 8b.

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#69

Hello (again) from the Gemma team! We are quite excited to push this release out and happy to answer any questions! Opinions are our own and not of Google DeepMind.

It's fairly easy to pay OpenAI or Mistral money to use their API's. Figuring out how Google Cloud Vertex works and how it's billed is more complicated. Azure and AWS are similar in how complex they are to use for this. Could Google Cloud please provide an OpenAI compatible API and service? I know it's a different department. But it'd make using your models way easier. It often feels like Google Cloud has no UX or end…

I have to agree with all of this. I tried switching to Gemini, but the lack of clear billing/quotas, horrible documentation, and even poor implementation of status codes on failed requests have led me to stick with OpenAI.

I don't know who writes Google's documentation or does the copyediting for their console, but it is hard to adapt. I have spent hours troubleshooting, only to find out it's because the documentation is referring to the same thing by two different names. It's 2024 also, I shouldn't be seeing print statements without parentheses.

Re: Gemma 2: Improving Open Language Models at a Practical Size [pdf]

#70

Hello (again) from the Gemma team! We are quite excited to push this release out and happy to answer any questions! Opinions are our own and not of Google DeepMind.

Any gemma-2-9b or 27b 4 bit GGUF's on HuggingFace yet? Thanks!

Actually for the 9B model, this has 4-bit quantised weights (and others): https://huggingface.co/bartowski/gemma-2-9b-it-GGUF

Still no 27B 4-bit GGUF quants on HF yet!

I'm monitoring this search: https://huggingface.co/models?library=gguf&sort=trending&sea...

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