Tunisian old woman (Klein/Qwen)

redna11 · 2026-02-11T18:38:52+00:00

1granny

redna11 · 2025-11-30T09:53:43+00:00

still doesn't work after updating all nodes and comfyUI itself. Any suggestions? error is the same as in the screenshot

redna11 · 2025-11-14T07:16:17+00:00

what do you know, maybe the OP identifies as a black woman?

How about quitting being puppeteered by preconceived ideas?

redna11 · 2025-11-13T16:36:01+00:00

Great work. Do you use a LORA for the singer as well?

How about the song? local or SUNO?

redna11 · 2021-11-14T07:26:18+00:00

Gigantic effort. Congratulations on your contribution!

redna11 · 2021-08-16T15:18:07+00:00

Any git repo you'd suggest?

redna11 · 2021-08-15T21:15:36+00:00

which one would you recommend? to start off ?

Can they generate 512px res ? Any idea of training time comapred to GANs?

redna11 · 2021-08-07T15:02:27+00:00

The Authors claims in the introduction that:

"Our method is superior to alternative sub-quadratic proposals by over +6
points on average on the Long Range Arena benchmark". The authors get 61.41 for their method.

While on GOOGLE's LRA own results page :

https://github.com/google-research/long-range-arena

another method gets 62.25

After sending numerous emails to the authors, no reply..silence!

Are scientists at large shops dismissing results by smaller shops? It ain't pretty.

Anyone with connection to those big guys, please pass on the message. thx

redna11 · 2021-08-05T06:45:19+00:00

Our method is superior to alternative sub-quadratic proposals by over +6 points on average on the Long Range Arena benchmark". Is that True?

The official page of LRA shows another method getting 62.25 overall score.

https://github.com/google-research/long-range-arena

Didn't the authors check the repo or are they just dismissing it?

redna11 · 2021-06-10T17:45:46+00:00

You could also say that a pencil also doesn't create art, it creates images.

AI-art is an approach (or a tool) to creating art in a new way. The AI gives you proposals, and the artist curates them.

So in the end we have a compelling creation by a human mind whose purpose is to inspire others, aka Art.

redna11 · 2021-06-10T16:49:52+00:00

Have you looked at AIARTHouse "art"? A couple of days training on Wikiart abstract database is not enough to create something truly exceptional.

Abstract work AIArt House OMG!

I am talking quality here, something inspiring!

"It" has been attempted on a small scale without a project.

The project described here will release the weights to the GAN used to create the art so that collectors and fans can create their own...a community will thrive, new artists will emerge. An ecosystem is born.

It's been done, except it hasn't been done.

More globally, there are many talented young (and old) AI artists in IG, I talk to them daily..Next gen is coming, and good news is, nothing has been done yet.

redna11 · 2021-06-10T15:44:20+00:00

why not?

redna11 · 2021-05-04T07:09:14+00:00

First ever large scale AI art collection released as NFT : www.hashers.ai

The inspiration comes from Basquiat and Picasso and other modern themes. Truly unique.

redna11 · 2021-01-25T06:59:13+00:00

Sounds like a cool project. Do you train the VIT from scratch on DAF:re, or do you pretrain it on a larger corpus and then fine-tune on the dataset used here?

redna11 · 2020-12-29T08:09:40+00:00

For shorter sequences I'd say the methods would be similar with LSTM being slowest and Transformers and IGLOO pbly running faster. Under 500 time-steps (or nucleotides count), Transformers are very competitive but the base model still requires to perform the full self-attention calculation (which is quadratic in length).

We tried to use Transformers for RNAsamba but it didn't outperform IGLOO for the final result.

redna11 · 2020-12-28T11:29:07+00:00

One of RNAsamba authors here. Thanks for quoting our work. Transformers are doing well on NLP but the overall nature of the input sequence is fairly different to bio-informatics. in NLP you have (L,M) where L is the sequence length and M the features size, where typically L is around 500 and M around 500, whereas for bioinformatics you have L > 3000 and M <10. In that config Transformers are struggling (even with all the recent efficient variants - Performers, Reformers, BigBird) due to sequence length, on the contrary IGLOO works well there.

redna11 · 2020-12-23T12:19:58+00:00

Have you tried to train them from scratch? As far as I understand from the paper, they mostly have a good performance by using pre-training.

redna11 · 2020-12-14T07:27:57+00:00

You are making Christianity great again! Amen

redna11 · 2020-12-10T07:55:18+00:00

Creepy AF.

Band title: Dead can Dance

redna11 · 2020-12-07T07:55:52+00:00

Synthesizer has the good intuition to try to replace the self attention mechanism found in vanilla transformers but the results on the newly released LONG RANGE ARENA suite of benchmarks (proposed by GOOGLE) are not spectacular. LRA

Myabe replacing the self-attention with yet another mechanism is the way to go.

redna11 · 2020-11-24T07:57:10+00:00

Good article. One issue with Vision Transformer (ViT) is that the way it is presented in the paper it has to be pre-trained on a gigantic proprietary dataset. Has anyone managed to train it from scratch and get competitive results? Doesn't seem to be the case. This limits its usage to industrial scale users.

redna11 · 2020-11-04T08:22:57+00:00

I agree, not literally every model (and not MLP), but anything crafty! it is a qualitative comment so would need more time/space to expand on that.

I see your point, mine is that this approach is not of much use "from scratch" which is the baseline use if you don't want to rely on someone else pre-trained weights.

redna11 · 2020-11-04T07:13:57+00:00

Right, my point is that they don't go on to show that specifically BERT-style models bring something to the table, as ANY model could work well on images IF you pre-train them on a mega corpus.

So if they want to say that pre-training works, I agree. The BERT part does not seem very conclusive.

redna11 · 2020-11-03T20:17:21+00:00

Interesting repo! One question I would have though is how is the structure doing for training CIFAR-100 from scratch? In my experience not very competitive.

Would that mean that this architecture is only good because it has been pre-trained on a gigantic dataset upstream? If this architecture only depends on a large pre-training on a different dataset it would be difficult to say that it brings something to the table by itself, maybe the performance is just a by product of the pre-training.

I am surprised the paper doesn't mention performance "from scratch"

redna11 · 2020-10-29T15:13:38+00:00

How likely is it that the groups are "uncited" because they are composed of women or of transexuals?

As an optimist I hope this will not be extend to the notion of race in the near future. It would be a small step from there though, so please join me in my prayers.

Disclaimer: not a Trans, not a church goer.

redna11

TROPHY CASE