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Parti - Scaling Autoregressive Models for Content-Rich Text-to-Image Generation (Paper Explained)

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Manage episode 332855034 series 2974171
Contenuto fornito da Yannic Kilcher. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Yannic Kilcher o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

#parti #ai #aiart

Parti is a new autoregressive text-to-image model that shows just how much scale can achieve. This model's outputs are crips, accurate, realistic, and can combine arbitrary styles, concepts, and fulfil even challenging requests.

OUTLINE:

0:00 - Introduction

2:40 - Example Outputs

6:00 - Model Architecture

17:15 - Datasets (incl. PartiPrompts)

21:45 - Experimental Results

27:00 - Picking a cherry tree

29:30 - Failure cases

33:20 - Final comments

Website: https://parti.research.google/

Paper: https://arxiv.org/abs/2206.10789

Github: https://github.com/google-research/parti

Links:

Homepage: https://ykilcher.com

Merch: https://ykilcher.com/merch

YouTube: https://www.youtube.com/c/yannickilcher

Twitter: https://twitter.com/ykilcher

Discord: https://ykilcher.com/discord

LinkedIn: https://www.linkedin.com/in/ykilcher

If you want to support me, the best thing to do is to share out the content :)

If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this):

SubscribeStar: https://www.subscribestar.com/yannick...

Patreon: https://www.patreon.com/yannickilcher

Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq

Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2

Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m

Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

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177 episodi

Artwork
iconCondividi
 
Manage episode 332855034 series 2974171
Contenuto fornito da Yannic Kilcher. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Yannic Kilcher o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

#parti #ai #aiart

Parti is a new autoregressive text-to-image model that shows just how much scale can achieve. This model's outputs are crips, accurate, realistic, and can combine arbitrary styles, concepts, and fulfil even challenging requests.

OUTLINE:

0:00 - Introduction

2:40 - Example Outputs

6:00 - Model Architecture

17:15 - Datasets (incl. PartiPrompts)

21:45 - Experimental Results

27:00 - Picking a cherry tree

29:30 - Failure cases

33:20 - Final comments

Website: https://parti.research.google/

Paper: https://arxiv.org/abs/2206.10789

Github: https://github.com/google-research/parti

Links:

Homepage: https://ykilcher.com

Merch: https://ykilcher.com/merch

YouTube: https://www.youtube.com/c/yannickilcher

Twitter: https://twitter.com/ykilcher

Discord: https://ykilcher.com/discord

LinkedIn: https://www.linkedin.com/in/ykilcher

If you want to support me, the best thing to do is to share out the content :)

If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this):

SubscribeStar: https://www.subscribestar.com/yannick...

Patreon: https://www.patreon.com/yannickilcher

Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq

Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2

Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m

Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

  continue reading

177 episodi

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