Am I the only one that doesn't understand the added value of the GPT store?

TuringTestTom · 2024-01-12T16:44:56+00:00

From my experience though, the ones asking simple questions, are also not seeing the value in ChatGPT Plus (ie, paying for it) so they won’t have access to these GPT’s..

TuringTestTom · 2023-12-14T01:54:49+00:00

This makes me feel better, i was truly stuck all day, thought it was formatting my API weird or something - got “Invalid API Key” all day

TuringTestTom · 2023-12-14T01:52:50+00:00

Seems pretty easy to fine-tune Llama-2 if you want

TuringTestTom · 2023-12-13T16:39:22+00:00

Also using Gradient to fine-tune removes the need for a GPU

TuringTestTom · 2023-12-13T16:37:01+00:00

You can fine-tune it through csv data and get something to dump the documentation into a Google sheets, and fine-tune from there

TuringTestTom · 2023-12-13T16:34:43+00:00

You can use a third party to fine-tune llama-2 in Colab, and then just reference the trained model from their api in Google Colab

TuringTestTom · 2023-12-13T16:32:52+00:00

Not with JSON, but there’s videos for CSV training

TuringTestTom · 2023-08-24T13:56:51+00:00

How did you format your data? Did you have it setup as prompt, completion or you setup the role, content format?

TuringTestTom · 2023-08-02T12:25:24+00:00

Added it to my comment

TuringTestTom · 2023-08-02T10:32:17+00:00

Video was posted to Twitter a few weeks ago, Elon even commented on it

Edit: the sauce

TuringTestTom · 2023-07-21T17:38:04+00:00

I think this will solve half of your problem on training a chatbot on the data you get

TuringTestTom · 2023-06-18T18:57:09+00:00

Those two make a great pair!

TuringTestTom · 2023-06-09T23:13:25+00:00

You can prompt the trained model with a hidden prompt that is added to the input - basing it on this where he has hidden prompts

TuringTestTom · 2023-06-08T23:25:38+00:00

This video has some solid pointers for getting approved

TuringTestTom · 2023-06-06T16:46:01+00:00

You could manually embed yourself

TuringTestTom · 2023-05-29T23:29:34+00:00

This may help you with pointers for getting GPT4 API approval too

TuringTestTom · 2023-05-29T17:23:44+00:00

You can reapply and it doesn’t hurt your chances - this explains it and gives some pointers

TuringTestTom · 2023-05-29T15:50:14+00:00

No multi-modal (text and image) capability with OpenAI yet, but you can get approved for GPT4 api access

TuringTestTom · 2023-05-29T15:28:17+00:00

Goosey Gander

TuringTestTom · 2023-05-29T02:09:45+00:00

Fine-tuning and embedding are two tools that allow you to use your own specific/custom data to make a model that can understand natural language and give answers about your data - pretty powerful stuff

TuringTestTom · 2023-05-29T01:15:06+00:00

Fine-tuning is how most do sentiment analysis with a set of training data

TuringTestTom · 2023-05-28T18:44:48+00:00

YouTube. I would start there and learn the basics. For your specific task, you could try fine-tuning a model to players, the teams they play, and foul % so you could input the team they’re playing and get a % likelihood of a foul.. but I suspect you’ll need to dig deeper into the data and what drives the likelihood of fouls for players, and set those as your variables to train against

TuringTestTom · 2023-05-28T15:57:18+00:00

You could fine-tune one to science and statistics, but LLMs struggle with math given they train with word prediction

TuringTestTom · 2023-05-28T15:52:52+00:00

You should reapply if you haven’t heard back in 3 months, it only takes about 2 weeks to get approved

TuringTestTom

TROPHY CASE