mirror of
https://github.com/lucidrains/DALLE2-pytorch.git
synced 2026-02-18 12:24:41 +01:00
Compare commits
2 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
0692f1699f | ||
|
|
26c4534bc3 |
@@ -214,8 +214,6 @@ Let's see the whole script below
|
|||||||
import torch
|
import torch
|
||||||
from dalle2_pytorch import DALLE2, DiffusionPriorNetwork, DiffusionPrior, Unet, Decoder, CLIP
|
from dalle2_pytorch import DALLE2, DiffusionPriorNetwork, DiffusionPrior, Unet, Decoder, CLIP
|
||||||
|
|
||||||
import torch
|
|
||||||
|
|
||||||
clip = CLIP(
|
clip = CLIP(
|
||||||
dim_text = 512,
|
dim_text = 512,
|
||||||
dim_image = 512,
|
dim_image = 512,
|
||||||
@@ -303,6 +301,8 @@ images = dalle2(['cute puppy chasing after a squirrel'])
|
|||||||
|
|
||||||
Everything in this readme should run without error
|
Everything in this readme should run without error
|
||||||
|
|
||||||
|
For the layperson, no worries, training will all be automated into a CLI tool, at least for small scale training.
|
||||||
|
|
||||||
## Training CLI (wip)
|
## Training CLI (wip)
|
||||||
|
|
||||||
<a href="https://github.com/lucidrains/stylegan2-pytorch">template</a>
|
<a href="https://github.com/lucidrains/stylegan2-pytorch">template</a>
|
||||||
@@ -364,3 +364,5 @@ Everything in this readme should run without error
|
|||||||
primaryClass = {cs.LG}
|
primaryClass = {cs.LG}
|
||||||
}
|
}
|
||||||
```
|
```
|
||||||
|
|
||||||
|
*Creating noise from data is easy; creating data from noise is generative modeling.* - Yang Song's <a href="https://arxiv.org/abs/2011.13456">paper</a>
|
||||||
|
|||||||
Reference in New Issue
Block a user