Mirrors
/
diffusers
mirror of https://github.com/ShivamShrirao/diffusers.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Fix some little typos

This commit is contained in:
milyiyo 2022-06-15 20:23:27 -04:00 committed by GitHub
parent 7d4bafa8a4
commit c5e54c200a
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
README.md
View File

@ -47,7 +47,7 @@ The class provides functionality to compute previous image according to alpha, b
## Philosophy
- Readability and clarity is prefered over highly optimized code. A strong importance is put on providing readable, intuitive and elementary code desgin. *E.g.*, the provided [schedulers](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers) are separated from the provided [models](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models) and provide well-commented code that can be read alongside the original paper.
- Readability and clarity is prefered over highly optimized code. A strong importance is put on providing readable, intuitive and elementary code design. *E.g.*, the provided [schedulers](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers) are separated from the provided [models](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models) and provide well-commented code that can be read alongside the original paper.
- Diffusers is **modality independent** and focusses on providing pretrained models and tools to build systems that generate **continous outputs**, *e.g.* vision and audio.
- Diffusion models and schedulers are provided as consise, elementary building blocks whereas diffusion pipelines are a collection of end-to-end diffusion systems that can be used out-of-the-box, should stay as close as possible to their original implementation and can include components of other library, such as text-encoders. Examples for diffusion pipelines are [Glide](https://github.com/openai/glide-text2im) and [Latent Diffusion](https://github.com/CompVis/latent-diffusion).
@ -174,7 +174,7 @@ image_pil = PIL.Image.fromarray(image_processed[0])
image_pil.save("test.png")
```
### 2. `diffusers` as a collection of popula Diffusion systems (GLIDE, Dalle, ...)
### 2. `diffusers` as a collection of popular Diffusion systems (GLIDE, Dalle, ...)
For more examples see [pipelines](https://github.com/huggingface/diffusers/tree/main/src/diffusers/pipelines).