111–120 of 252 posts
Does anyone have a good layman's explanation of the "Mixture-of-Experts" concept? I think I understand the idea of having "sub-experts", but how do you decide what each specialization is during training? Or is that not how it works at all?
These LLMs are making RAM great again. Wish I had invested in the extra 32GB for my mac laptop.
You can't upgrade it? Edit: I haven't owned a laptop for years, probably could have surmised they'd be more user hostile nowadays.
Output: https://gist.github.com/IAmStoxe/7fb224225ff13b1902b6d172467...
Within the first paragraph, it outputs:
> GET AN ESSAY WRITTEN FOR YOU FROM AS LOW AS $13/PAGE
Thought that was hilarious.
What's the best way to run this on my Macbook Pro? I've tried LMStudio, but I'm not a fan of the interface compared to OpenAI's. The lack of automatic regeneration every time I edit my input, like on ChatGPT, is quite frustrating. I also gave Ollama a shot, but using the CLI is less convenient. Ideally, I'd like something that allows me to edit my settings quite granularly, similar to what I can do in OpenLM, with th…
Ollama with WebUI https://github.com/open-webui/open-webui
Open WebUI is functionally identical to the ChatGPT interface. You can even use it with the OpenAI APIs to have your own pay per use GPT 4. I did this.
I'm considering switching my function calling requests from OpenAI's API to Mistral. Are they using similar formats? What's the easiest way to use Mistral? Is it by using Huggingface?
easiest is probably with ollama [0]. I think the ollama API is OpenAI compatible. [0] https://ollama.com/
Earlier quoted context omitted.
You can't upgrade it? Edit: I haven't owned a laptop for years, probably could have surmised they'd be more user hostile nowadays.
Everything is soldered in these days. It's complete garbage. And most of the other vendors just copy Apple so even things like Lenovo have the same problems. The current state of laptops is such trash
"64K tokens context window" I do wish they had managed to extend it to at least 128K to match the capabilities of GPT-4 Turbo Maybe this limit will become a joke when looking back? Can you imagine reaching a trillion tokens context window in the future, as Sam speculated on Lex's podcast?
maybe we'll look back at token context windows like we look back at how much ram we have in a system.
If we have cheap billion token context windows, 99% of your use cases aren't going to hit anywhere close to that limit and as a result, your models will "just run"
First test I tried to run a random taxation question through it Output: https://gist.github.com/IAmStoxe/7fb224225ff13b1902b6d172467... Within the first paragraph, it outputs: > GET AN ESSAY WRITTEN FOR YOU FROM AS LOW AS $13/PAGE Thought that was hilarious.