---
title: Others
---
# :fontawesome-regular-share-from-square: Others
## **Google Colab**
Stable Diffusion AI Notebook:
Open and follow instructions to use an isolated environment running
Dream.
Output Example: 
---
## **Seamless Tiling**
The seamless tiling mode causes generated images to seamlessly tile with itself. To use it, add the
`--seamless` option when starting the script which will result in all generated images to tile, or
for each `dream>` prompt as shown here:
```python
dream> "pond garden with lotus by claude monet" --seamless -s100 -n4
```
---
## **Shortcuts: Reusing Seeds**
Since it is so common to reuse seeds while refining a prompt, there is now a shortcut as of version
1.11. Provide a `**-S**` (or `**--seed**`) switch of `-1` to use the seed of the most recent image
generated. If you produced multiple images with the `**-n**` switch, then you can go back further
using -2, -3, etc. up to the first image generated by the previous command. Sorry, but you can't go
back further than one command.
Here's an example of using this to do a quick refinement. It also illustrates using the new `**-G**`
switch to turn on upscaling and face enhancement (see previous section):
```bash
dream> a cute child playing hopscotch -G0.5
[...]
outputs/img-samples/000039.3498014304.png: "a cute child playing hopscotch" -s50 -W512 -H512 -C7.5 -mk_lms -S3498014304
# I wonder what it will look like if I bump up the steps and set facial enhancement to full strength?
dream> a cute child playing hopscotch -G1.0 -s100 -S -1
reusing previous seed 3498014304
[...]
outputs/img-samples/000040.3498014304.png: "a cute child playing hopscotch" -G1.0 -s100 -W512 -H512 -C7.5 -mk_lms -S3498014304
```
---
## **Simplified API**
For programmers who wish to incorporate stable-diffusion into other products, this repository
includes a simplified API for text to image generation, which lets you create images from a prompt
in just three lines of code:
```bash
from ldm.generate import Generate
g = Generate()
outputs = g.txt2img("a unicorn in manhattan")
```
Outputs is a list of lists in the format [filename1,seed1],[filename2,seed2]...].
Please see ldm/generate.py for more information. A set of example scripts is coming RSN.
---
## **Preload Models**
In situations where you have limited internet connectivity or are blocked behind a firewall, you can
use the preload script to preload the required files for Stable Diffusion to run.
The preload script `scripts/preload_models.py` needs to be run once at least while connected to the
internet. In the following runs, it will load up the cached versions of the required files from the
`.cache` directory of the system.
```bash
(ldm) ~/stable-diffusion$ python3 ./scripts/preload_models.py
preloading bert tokenizer...
Downloading: 100%|██████████████████████████████████| 28.0/28.0 [00:00<00:00, 49.3kB/s]
Downloading: 100%|██████████████████████████████████| 226k/226k [00:00<00:00, 2.79MB/s]
Downloading: 100%|██████████████████████████████████| 455k/455k [00:00<00:00, 4.36MB/s]
Downloading: 100%|██████████████████████████████████| 570/570 [00:00<00:00, 477kB/s]
...success
preloading kornia requirements...
Downloading: "https://github.com/DagnyT/hardnet/raw/master/pretrained/train_liberty_with_aug/checkpoint_liberty_with_aug.pth" to /u/lstein/.cache/torch/hub/checkpoints/checkpoint_liberty_with_aug.pth
100%|███████████████████████████████████████████████| 5.10M/5.10M [00:00<00:00, 101MB/s]
...success
```