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Sep 23, 2022
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docs: .md readability fixups #619

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2 changes: 1 addition & 1 deletion docs/source/api/pipelines/overview.mdx
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Expand Up @@ -85,7 +85,7 @@ not be used for training. If you want to store the gradients during the forward
We are more than happy about any contribution to the officially supported pipelines 🤗. We aspire
all of our pipelines to be **self-contained**, **easy-to-tweak**, **beginner-friendly** and for **one-purpose-only**.

- **Self-contained**: A pipeline shall be as self-contained as possible. More specifically, this means that all functionality should be either directly defined in the pipeline file iteslf, should be inherited from (and only from) the [`DiffusionPipeline` class](.../diffusion_pipeline) or be directly attached to the model and scheduler components of the pipeline.
- **Self-contained**: A pipeline shall be as self-contained as possible. More specifically, this means that all functionality should be either directly defined in the pipeline file itself, should be inherited from (and only from) the [`DiffusionPipeline` class](.../diffusion_pipeline) or be directly attached to the model and scheduler components of the pipeline.
- **Easy-to-use**: Pipelines should be extremely easy to use - one should be able to load the pipeline and
use it for its designated task, *e.g.* text-to-image generation, in just a couple of lines of code. Most
logic including pre-processing, an unrolled diffusion loop, and post-processing should all happen inside the `__call__` method.
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2 changes: 1 addition & 1 deletion docs/source/using-diffusers/configuration.mdx
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Expand Up @@ -27,6 +27,6 @@ pip install diffusers

### Schedulers

### Pipeliens
### Pipelines


2 changes: 1 addition & 1 deletion docs/source/using-diffusers/unconditional_image_generation.mdx
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Expand Up @@ -12,7 +12,7 @@ specific language governing permissions and limitations under the License.



# Unonditional Image Generation
# Unconditional Image Generation

The [`DiffusionPipeline`] is the easiest way to use a pre-trained diffusion system for inference

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2 changes: 1 addition & 1 deletion src/diffusers/pipelines/README.md
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Expand Up @@ -73,7 +73,7 @@ not be used for training. If you want to store the gradients during the forward
We are more than happy about any contribution to the officially supported pipelines 🤗. We aspire
all of our pipelines to be **self-contained**, **easy-to-tweak**, **beginner-friendly** and for **one-purpose-only**.

- **Self-contained**: A pipeline shall be as self-contained as possible. More specifically, this means that all functionality should be either directly defined in the pipeline file iteslf, should be inherited from (and only from) the [`DiffusionPipeline` class](https://github.com/huggingface/diffusers/blob/5cbed8e0d157f65d3ddc2420dfd09f2df630e978/src/diffusers/pipeline_utils.py#L56) or be directly attached to the model and scheduler components of the pipeline.
- **Self-contained**: A pipeline shall be as self-contained as possible. More specifically, this means that all functionality should be either directly defined in the pipeline file itself, should be inherited from (and only from) the [`DiffusionPipeline` class](https://github.com/huggingface/diffusers/blob/5cbed8e0d157f65d3ddc2420dfd09f2df630e978/src/diffusers/pipeline_utils.py#L56) or be directly attached to the model and scheduler components of the pipeline.
- **Easy-to-use**: Pipelines should be extremely easy to use - one should be able to load the pipeline and
use it for its designated task, *e.g.* text-to-image generation, in just a couple of lines of code. Most
logic including pre-processing, an unrolled diffusion loop, and post-processing should all happen inside the `__call__` method.
Expand Down