From 2b8261c7eaa1538648234b4bdcebe3d830943ddb Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Tue, 16 Aug 2022 21:40:40 -0400 Subject: [PATCH] fixing formatting in readme --- README.md | 56 +++++++++++++++++++++++++++++++------------------------ 1 file changed, 32 insertions(+), 24 deletions(-) diff --git a/README.md b/README.md index 84f06b1435..2029a6a537 100644 --- a/README.md +++ b/README.md @@ -29,28 +29,33 @@ fast. Note that this has only been tested in the Linux environment! - (ldm) ~/stable-diffusion$ ./scripts/dream.py - * Initializing, be patient... +~~~~ +(ldm) ~/stable-diffusion$ ./scripts/dream.py +* Initializing, be patient... +Loading model from models/ldm/text2img-large/model.ckpt +LatentDiffusion: Running in eps-prediction mode +DiffusionWrapper has 872.30 M params. +making attention of type 'vanilla' with 512 in_channels +Working with z of shape (1, 4, 32, 32) = 4096 dimensions. +making attention of type 'vanilla' with 512 in_channels +Loading Bert tokenizer from "models/bert" +setting sampler to plms - Loading model from models/ldm/text2img-large/model.ckpt - LatentDiffusion: Running in eps-prediction mode - DiffusionWrapper has 872.30 M params. - making attention of type 'vanilla' with 512 in_channels - Working with z of shape (1, 4, 32, 32) = 4096 dimensions. - making attention of type 'vanilla' with 512 in_channels - Loading Bert tokenizer from "models/bert" - setting sampler to plms +* Initialization done! Awaiting your command... +dream> ashley judd riding a camel -n2 +Outputs: + outputs/txt2img-samples/00009.png: "ashley judd riding a camel" -n2 -S 416354203 + outputs/txt2img-samples/00010.png: "ashley judd riding a camel" -n2 -S 1362479620 - * Initialization done! Awaiting your command... - dream> ashley judd riding a camel -n2 - Outputs: - outputs/txt2img-samples/00009.png: "ashley judd riding a camel" -n2 -S 416354203 - outputs/txt2img-samples/00010.png: "ashley judd riding a camel" -n2 -S 1362479620 +dream> "your prompt here" -n6 -g +... +~~~~ -Command-line arguments ("./scripts/dream.py -h") allow you to change +Command-line arguments (`./scripts/dream.py -h`) allow you to change various defaults, and select between the mature stable-diffusion weights (512x512) and the older (256x256) latent diffusion weights -(laion400m). +(laion400m). Within the script, the switches are (mostly) identical to +those used in the Discord bot, except you don't need to type "!dream". ## No need for internet connectivity when loading the model @@ -64,11 +69,13 @@ expedient thing to do was to download the Bert tokenizer in advance, and patch stable-diffusion to read it from the local disk. The steps to do this are: - (ldm) ~/stable-diffusion$ mkdir ./models/bert - > python3 - >>> from transformers import BertTokenizerFast - >>> model = BertTokenizerFast.from_pretrained("bert-base-uncased") - >>> model.save_pretrained("./models/bert") +~~~~ +(ldm) ~/stable-diffusion$ mkdir ./models/bert +> python3 +>>> from transformers import BertTokenizerFast +>>> model = BertTokenizerFast.from_pretrained("bert-base-uncased") +>>> model.save_pretrained("./models/bert") +~~~~ (Make sure you are in the stable-diffusion directory when you do this!) @@ -85,9 +92,10 @@ I added the requirement for torchmetrics to environment.yaml. Follow the directions from the original README, which starts below, to configure the environment and install requirements. For support, -please use this repository's GitHub Issues tracking service. +please use this repository's GitHub Issues tracking service. Feel free +to send me an email if you use and like the script. -Author: Lincoln D. Stein +*Author:* Lincoln D. Stein # Original README from CompViz/stable-diffusion *Stable Diffusion was made possible thanks to a collaboration with [Stability AI](https://stability.ai/) and [Runway](https://runwayml.com/) and builds upon our previous work:*