diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 0aa2a77dbc..049d317599 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -57,7 +57,7 @@ Any question or comment related to the Diffusers library can be asked on the [di - ... Every question that is asked on the forum or on Discord actively encourages the community to publicly -share knowledge and might very well help a beginner in the future that has the same question you're +share knowledge and might very well help a beginner in the future who has the same question you're having. Please do pose any questions you might have. In the same spirit, you are of immense help to the community by answering such questions because this way you are publicly documenting knowledge for everybody to learn from. @@ -503,4 +503,4 @@ $ git push --set-upstream origin your-branch-for-syncing ### Style guide -For documentation strings, 🧨 Diffusers follows the [Google style](https://google.github.io/styleguide/pyguide.html). \ No newline at end of file +For documentation strings, 🧨 Diffusers follows the [Google style](https://google.github.io/styleguide/pyguide.html). diff --git a/PHILOSOPHY.md b/PHILOSOPHY.md index 9e25b4cc6d..e85182ab46 100644 --- a/PHILOSOPHY.md +++ b/PHILOSOPHY.md @@ -15,7 +15,7 @@ specific language governing permissions and limitations under the License. 🧨 Diffusers provides **state-of-the-art** pretrained diffusion models across multiple modalities. Its purpose is to serve as a **modular toolbox** for both inference and training. -We aim at building a library that stands the test of time and therefore take API design very seriously. +We aim to build a library that stands the test of time and therefore take API design very seriously. In a nutshell, Diffusers is built to be a natural extension of PyTorch. Therefore, most of our design choices are based on [PyTorch's Design Principles](https://pytorch.org/docs/stable/community/design.html#pytorch-design-philosophy). Let's go over the most important ones: @@ -107,4 +107,4 @@ The following design principles are followed: - Every scheduler exposes the timesteps to be "looped over" via a `timesteps` attribute, which is an array of timesteps the model will be called upon. - The `step(...)` function takes a predicted model output and the "current" sample (x_t) and returns the "previous", slightly more denoised sample (x_t-1). - Given the complexity of diffusion schedulers, the `step` function does not expose all the complexity and can be a bit of a "black box". -- In almost all cases, novel schedulers shall be implemented in a new scheduling file. \ No newline at end of file +- In almost all cases, novel schedulers shall be implemented in a new scheduling file. diff --git a/docs/source/en/stable_diffusion.md b/docs/source/en/stable_diffusion.md index db4953ebbf..64d8f7df0b 100644 --- a/docs/source/en/stable_diffusion.md +++ b/docs/source/en/stable_diffusion.md @@ -238,7 +238,7 @@ Pretty impressive! Let's tweak the second image - corresponding to the `Generato ```python prompts = [ "portrait photo of the oldest warrior chief, tribal panther make up, blue on red, side profile, looking away, serious eyes 50mm portrait photography, hard rim lighting photography--beta --ar 2:3 --beta --upbeta", - "portrait photo of a old warrior chief, tribal panther make up, blue on red, side profile, looking away, serious eyes 50mm portrait photography, hard rim lighting photography--beta --ar 2:3 --beta --upbeta", + "portrait photo of an old warrior chief, tribal panther make up, blue on red, side profile, looking away, serious eyes 50mm portrait photography, hard rim lighting photography--beta --ar 2:3 --beta --upbeta", "portrait photo of a warrior chief, tribal panther make up, blue on red, side profile, looking away, serious eyes 50mm portrait photography, hard rim lighting photography--beta --ar 2:3 --beta --upbeta", "portrait photo of a young warrior chief, tribal panther make up, blue on red, side profile, looking away, serious eyes 50mm portrait photography, hard rim lighting photography--beta --ar 2:3 --beta --upbeta", ]