biggieshiba t1_jednwqo wrote on March 31, 2023 at 7:02 AM

Reply to [P] Introducing Vicuna: An open-source language model based on LLaMA 13B by Business-Lead2679

So how much a100 did it take to train?

biggieshiba t1_jdojnn6 wrote on March 25, 2023 at 11:28 PM

Reply to comment by hangtime79 in [R] Hello Dolly: Democratizing the magic of ChatGPT with open models by austintackaberry

I don't understand why anyone would care, in a few years half the internet will be ai generated. If someone uses GPT-4 to generate a sentence posted on Wikipedia how will you know before using it ? Don't you think many models will use that sentence?

Plus, how will they know, training data is not easy to extract from a model. Except if you are a direct OpenAI competitor they won't ever care or even look at you (well maybe their superAI will).

Lastly the dataset is full of errors, better generate again or even pay people would be quite cheap for 50k examples. This is quite a bad dataset when you really look at it, empty inputs or outputs, unclear instructions, instructions not fit for model... The fact that it is bad and small is very encouraging BTW since it performs pretty well.

biggieshiba t1_iub2sgl wrote on October 29, 2022 at 11:28 PM

Reply to comment by biggieshiba in [D] What are the bottlenecks in your ML project lifecycle? What tools would you like to see more widely used? by Fine-Topic-6127

(Or open source and a lot of effort)

biggieshiba t1_iub2r5m wrote on October 29, 2022 at 11:27 PM

Reply to comment by slippu in [D] What are the bottlenecks in your ML project lifecycle? What tools would you like to see more widely used? by Fine-Topic-6127

Then you need a ML expert to code python tools for you that encapsulate many tools with your preferred settings

biggieshiba t1_iub2lcd wrote on October 29, 2022 at 11:26 PM

Reply to comment by cantfindaname2take in [D] What are the bottlenecks in your ML project lifecycle? What tools would you like to see more widely used? by Fine-Topic-6127

Thanks mate I will learn this then. I find AwS is always a bit long to learn, but let's go, in the long run it always pays. Didn't want to go for something more complicated then I needed, I thought easier (and more expensive) services existed.

biggieshiba t1_iu8524i wrote on October 29, 2022 at 8:29 AM

Reply to [D] What are the bottlenecks in your ML project lifecycle? What tools would you like to see more widely used? by Fine-Topic-6127

Hello, I'm learning as a hobbyist and want to go to production with my trained model.

I know front and back end coding but serving and scaling a model in production seems daunting. I'm looking at AWS right now but it doesn't seem like the easiest tool to deploy ML models. I thought it would be much easier to deploy a model! (real world performance is another problem I will have to study soon)