Docs Update (#466)

Authored-by: @blessedcoolant 
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>

docs/features/OTHER.md

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+## **Google Colab**
+
+Stable Diffusion AI Notebook: <a href="https://colab.research.google.com/github/lstein/stable-diffusion/blob/main/Stable_Diffusion_AI_Notebook.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a> <br>
+Open and follow instructions to use an isolated environment running Dream.<br>
+
+Output Example:
+![Colab Notebook](../assets/colab_notebook.png)
+
+---
+
+## **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:
+
+```
+dream> "pond garden with lotus by claude monet" --seamless -s100 -n4
+```
+
+---
+
+## **Reading Prompts from a File**
+
+You can automate `dream.py` by providing a text file with the prompts you want to run, one line per prompt. The text file must be composed with a text editor (e.g. Notepad) and not a word processor. Each line should look like what you would type at the dream> prompt:
+
+```
+a beautiful sunny day in the park, children playing -n4 -C10
+stormy weather on a mountain top, goats grazing     -s100
+innovative packaging for a squid's dinner           -S137038382
+```
+
+Then pass this file's name to `dream.py` when you invoke it:
+
+```
+(ldm) ~/stable-diffusion$ python3 scripts/dream.py --from_file "path/to/prompts.txt"
+```
+
+You may read a series of prompts from standard input by providing a filename of `-`:
+
+```
+(ldm) ~/stable-diffusion$ echo "a beautiful day" | python3 scripts/dream.py --from_file -
+```
+
+---
+
+## **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):
+
+```
+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
+```
+
+---
+
+## **Weighted Prompts**
+
+You may weight different sections of the prompt to tell the sampler to attach different levels of
+priority to them, by adding `:(number)` to the end of the section you wish to up- or downweight.
+For example consider this prompt:
+
+```
+    tabby cat:0.25 white duck:0.75 hybrid
+```
+
+This will tell the sampler to invest 25% of its effort on the tabby cat aspect of the image and 75% on the white duck aspect (surprisingly, this example actually works). The prompt weights can
+use any combination of integers and floating point numbers, and they do not need to add up to 1.
+
+---
+
+## **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:
+
+```
+from ldm.simplet2i import T2I
+model   = T2I()
+outputs = model.txt2img("a unicorn in manhattan")
+```
+
+Outputs is a list of lists in the format [filename1,seed1],[filename2,seed2]...].
+
+Please see ldm/simplet2i.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.
+
+```
+(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
+```