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MiniGPT-4

minigpt-4.github.io

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Re: MiniGPT-4

#61

Post by Uehreka »

collaborative wrote: post #25
Tepix wrote: post #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.

Adding GPT4 to anything now increases marketing x4. So many AI news coming out lately that not adding it risks drowning in a sea of info.. even in the case of a good project

The word for this is “trademark infringement”. You are specifically not allowed to capitalize on the marketing of another entity’s product to bolster yours by implying through your name that you are somehow related. This is why “DALL-E Mini” had to change their name to craiyon.

Re: MiniGPT-4

#63

Post by MattPalmer1086 »

guax wrote: post #48
mjburgess wrote: post #17

Earlier quoted context omitted.

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)

And just like webdev, each of those were done in a different platform and require arcane incantations and 5h of doc perusing to make it work on your system.

You can just ask GPT how to do it. Much like a lot of web dev!

Re: MiniGPT-4

#64

Post by valine »

tarruda wrote: post #18

Looking forward to the next generation of cheap GPUs with enough VRAM to run models like Vicuna-13 locally.

Cheap is relative I suppose.

I’m running Vicuna 13b 16f locally and it needs 26GB of VRAM, which won’t even fit on a single RTX 4090. The next gen RTX Titan might have enough vram but that won’t come cheap. I’m expecting a price point above $2500.

Re: MiniGPT-4

#65

Post by tourgen »

pansa2 wrote: post #58
sho wrote: post #14

Earlier quoted context omitted.

> 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.

Web stuff probably makes ML devs feel the same way. ML is just a different field, using a different set of technologies from those you’re familiar with.

[dead]

Re: MiniGPT-4

#66

Post by seydor »

causi wrote: post #26
Tepix wrote: post #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.

Someone needs to write a buyer's guide for GPUs and LLMs. For example, what's the best course of action if don't need to train anything but do want to eventually run whatever model becomes the first local-capable equivalent to ChatGPT? Do you go with Nvidia for the CUDA cores or with AMD for more VRAM? Do you do neither and wait another generation?

At least for llama derivatives, reddit has a list https://www.reddit.com/r/LocalLLaMA/comments/11o6o3f/how_to_...

Re: MiniGPT-4

#67

Post by jack_riminton »

152334H wrote: post #39
selfhoster11 wrote: post #38

Earlier quoted context omitted.

Seriously, ChatGPT was the thing that gave me a foothold into the AI/machine learning world... because it gave me hope that a mere mortal can achieve something reasonable with this tech without a crazy amount of work and educational background.

I don't have much experience myself. I only started ~10 months ago -- just a month or two before Stable Diffusion. You just have to do it every day. It's fun!

Can you recommend what kind of small daily activities would help a web dev get into it?

Re: MiniGPT-4

#68

Post by sebzim4500 »

atgctg wrote: post #44

It's hard to distinguish non-Google projects with Google Sans in their templates from actual Google Research papers, as the font is meant to be exclusively used by Google[1]. [1] https://developers.google.com/fonts/faq#how_can_i_get_a_lice...

Surely most people would read the authors list to determine provenance rather than the font?

Re: MiniGPT-4

#69

Post by moffkalast »

causi wrote: post #21
omeid2 wrote: post #9

Earlier quoted context omitted.

What did you expect?

I never know what to expect anymore. We live in a world where computers can describe paintings and write sonnets about them but a half-trillion dollar car company can't figure out how to parallel park with eight cameras.

DriveGPT as it hits 2 parked cars and runs over a dog: "Apologies for the confusion earlier. You are correct that the cars were in the planned local planner path..."

Re: MiniGPT-4

#70

Post by Thomashuet »

m348e912 wrote: post #45
xnzakg wrote: post #31

The ramen example is kind of hilarious. Wonder if it would make more sense with a bigger model.

Ok I'll bite. What makes the Raman example so funny?

The recipe it suggests is completely off. Just search for "ramen recipe" and compare. For instance it tells you to add soy sauce, sesame oil and green onions to the broth (so far so good) but then tells you to throw all of it away ("once the noodles are cooked, drain them"). The problem here is that you should cook the noodles separately in plain water, not a broth with soy sauce.
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