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MiniGPT-4

minigpt-4.github.io

11–20 of 337 posts

Re: MiniGPT-4

#11
post #2

I don't know what unholy abomination they did to the scrolling, but after I increased the page font size, it just sticks to the bottom and you can't scroll up.

[deleted]

Re: MiniGPT-4

#12
I think it's poor form that they are taking the GPT-4 name for an unrelated project. After all, the underlying Vicuna is merely a fine-tuned LLaMA. Plus they use the smaller 13B version.

The results look interesting, however.

Here's hoping that they'll add GTPQ 4bit quantizing so the 65B version of the model can be run on 2x 3090.

Re: MiniGPT-4

#13

Earlier quoted context omitted.

1200s now...

Also some links don't seem to open in a new tab and if you click around while you wait you might lose your progress. I clicked on the Video button while waiting, assuming that it would open in a new tab, and lost my place in queue.

Also once you get your turn and ask your question, it puts you back in the queue.

Re: MiniGPT-4

#14
post #6

On a technical level, they're doing something really simple -- take BLIP2's ViT-L+Q-former, connect it to Vicuna-13B with a linear layer, and train just the tiny layer on some datasets of image-text pairs. But the results are pretty amazing. It completely knocks Openflamingo && even the original blip2 models out of the park. And best of all, it arrived before OpenAI's GPT-4 Image Modality did. Real win for Open Sourc…

> they're doing something really simple -- take BLIP2's ViT-L+Q-former, connect it to Vicuna-13B with a linear layer, and train just the tiny layer on some datasets of image-text pairs

Oh yes. Simple! Jesus, this ML stuff makes a humble web dev like myself feel like a dog trying to read Tolstoy.

Re: MiniGPT-4

#15
post #6

On a technical level, they're doing something really simple -- take BLIP2's ViT-L+Q-former, connect it to Vicuna-13B with a linear layer, and train just the tiny layer on some datasets of image-text pairs. But the results are pretty amazing. It completely knocks Openflamingo && even the original blip2 models out of the park. And best of all, it arrived before OpenAI's GPT-4 Image Modality did. Real win for Open Sourc…

Can any of this realistically run on CPU at some point?

(Not training obviously)

Re: MiniGPT-4

#16
post #2

I don't know what unholy abomination they did to the scrolling, but after I increased the page font size, it just sticks to the bottom and you can't scroll up.

Right off the bat I lost all scrolling inertia here, it's like being in the dark ages.

Re: MiniGPT-4

#17
post #14
post #6

On a technical level, they're doing something really simple -- take BLIP2's ViT-L+Q-former, connect it to Vicuna-13B with a linear layer, and train just the tiny layer on some datasets of image-text pairs. But the results are pretty amazing. It completely knocks Openflamingo && even the original blip2 models out of the park. And best of all, it arrived before OpenAI's GPT-4 Image Modality did. Real win for Open Sourc…

> they're doing something really simple -- take BLIP2's ViT-L+Q-former, connect it to Vicuna-13B with a linear layer, and train just the tiny layer on some datasets of image-text pairs Oh yes. Simple! Jesus, this ML stuff makes a humble web dev like myself feel like a dog trying to read Tolstoy.

In practice, it's a lot more like web dev than you might imagine.

The above means that the approach is web-dev like gluing, almost literally just,

    from existingliba import someop
    from existinglibb import anotherop
    from someaifw import glue

    a = someop(X)
    b = glue(a)
    Y = anotherop(b)

Re: MiniGPT-4

#19
post #14
post #6

On a technical level, they're doing something really simple -- take BLIP2's ViT-L+Q-former, connect it to Vicuna-13B with a linear layer, and train just the tiny layer on some datasets of image-text pairs. But the results are pretty amazing. It completely knocks Openflamingo && even the original blip2 models out of the park. And best of all, it arrived before OpenAI's GPT-4 Image Modality did. Real win for Open Sourc…

> they're doing something really simple -- take BLIP2's ViT-L+Q-former, connect it to Vicuna-13B with a linear layer, and train just the tiny layer on some datasets of image-text pairs Oh yes. Simple! Jesus, this ML stuff makes a humble web dev like myself feel like a dog trying to read Tolstoy.

Just get rid of all the abbreviations in your mind - they seem to be very intimidating. I really liked the explanation that Stephen Wolfram did on ChatGPT:

https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-...

Maybe someone has resources to understand machine-learning on an ELI5 level.

Re: MiniGPT-4

#20
post #6

On a technical level, they're doing something really simple -- take BLIP2's ViT-L+Q-former, connect it to Vicuna-13B with a linear layer, and train just the tiny layer on some datasets of image-text pairs. But the results are pretty amazing. It completely knocks Openflamingo && even the original blip2 models out of the park. And best of all, it arrived before OpenAI's GPT-4 Image Modality did. Real win for Open Sourc…

Thanks for a useful comment.

Do you reckon the 4bit quantized Vicuna just won't do here? https://huggingface.co/anon8231489123/vicuna-13b-GPTQ-4bit-1...

I think with this everything OpenAI demonstrated ~5 weeks ago has been recreated by actually-open AI. Even if it runs much much slower on prosumer hardware and with less good results at least it is de-magicked.

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