Merge pull request #25 from cclauss/patch-1

README.md: Fix typos

README.md

@@ -111,7 +111,7 @@ will be appended to a csv file `log/log.csv` in the `/sd` directory.
 
 If you're like me, you experiment a lot with prompts and settings, and only few images are worth saving. You can
 just save them using right click in browser, but then you won't be able to reproduce them later because you will not
-know what exact prompt created the image. If you use the flag button, generation paramerters will be written to csv file,
+know what exact prompt created the image. If you use the flag button, generation parameters will be written to csv file,
 and you can easily find parameters for an image by searching for its filename.
 
 ### Copy-paste generation parameters
@@ -123,7 +123,7 @@ If you generate multiple pictures, the displayed seed will be the seed of the fi
 
 ### Correct seeds for batches
 If you use a seed of 1000 to generate two batches of two images each, four generated images will have seeds: `1000, 1001, 1002, 1003`.
-Previous versions of the UI would produce `1000, x, 1001, x`, where x is an iamge that can't be generated by any seed.
+Previous versions of the UI would produce `1000, x, 1001, x`, where x is an image that can't be generated by any seed.
 
 ### Resizing
 There are three options for resizing input images in img2img mode:
@@ -167,7 +167,7 @@ PNG chunk info, for example: https://www.nayuki.io/page/png-file-chunk-inspector
 
 ### Textual Inversion
 Allows you to use pretrained textual inversion embeddings.
-See originial site for details: https://textual-inversion.github.io/.
+See original site for details: https://textual-inversion.github.io/.
 I used lstein's repo for training embdedding: https://github.com/lstein/stable-diffusion; if
 you want to train your own, I recommend following the guide on his site.