docs: correct typos in using-diffusers/other-formats

[Manith-Ratnayake]

What does this PR do?

Fixed two typos in
https://huggingface.co/docs/diffusers/en/using-diffusers/other-formats

Fix no 1:

Original Markdown:

turbo_pipeline.scheduler = EulerDiscreteScheduler.from_config(
    turbo_pipeline.scheduler.config,
    timestep+spacing="trailing"
)

The issue is the + symbol in the timestep+spacing. Replaced the + symbol with _
Update Markdown:

turbo_pipeline.scheduler = EulerDiscreteScheduler.from_config(
    turbo_pipeline.scheduler.config,
    timestep_spacing="trailing"
)

Fix no 2:

Original Markdown:

from huggingface_hub import export_folder_as_dduf
from diffusers import DiffusionPipeline
import torch 

pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)

save_folder = "flux-dev"
pipe.save_pretrained("flux-dev")
export_folder_as_dduf("flux-dev.dduf", folder_path=save_folder)

> [!TIP]
> Packaging and loading quantized checkpoints in the DDUF format is supported as long as they respect the multi-folder structure.

## Convert layout and files

Diffusers provides many scripts and methods to convert storage layouts and file formats to enable broader support across the diffusion ecosystem.

Take a look at the [diffusers/scripts](https://github.com/huggingface/diffusers/tree/main/scripts) collection to find a script that fits your conversion needs.

> [!TIP]
> Scripts that have "`to_diffusers`" appended at the end mean they convert a model to the Diffusers-multifolder layout. Each script has their own specific set of arguments for configuring the conversion, so make sure you check what arguments are available!

For example, to convert a Stable Diffusion XL model stored in Diffusers-multifolder layout to a single-file layout, run the [convert_diffusers_to_original_sdxl.py](https://github.com/huggingface/diffusers/blob/main/scripts/convert_diffusers_to_original_sdxl.py) script. Provide the path to the model to convert, and the path to save the converted model to. You can optionally specify whether you want to save the model as a safetensors file and whether to save the model in half-precision.

```bash
python convert_diffusers_to_original_sdxl.py --model_path path/to/model/to/convert --checkpoint_path path/to/save/model/to --use_safetensors

As you can see after the python code block started it is not closed.
Updated markdown:

from huggingface_hub import export_folder_as_dduf
from diffusers import DiffusionPipeline
import torch 

pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)

save_folder = "flux-dev"
pipe.save_pretrained("flux-dev")
export_folder_as_dduf("flux-dev.dduf", folder_path=save_folder)

Tip

Packaging and loading quantized checkpoints in the DDUF format is supported as long as they respect the multi-folder structure.

Convert layout and files

Diffusers provides many scripts and methods to convert storage layouts and file formats to enable broader support across the diffusion ecosystem.

Take a look at the diffusers/scripts collection to find a script that fits your conversion needs.

Tip

Scripts that have "to_diffusers" appended at the end mean they convert a model to the Diffusers-multifolder layout. Each script has their own specific set of arguments for configuring the conversion, so make sure you check what arguments are available!

For example, to convert a Stable Diffusion XL model stored in Diffusers-multifolder layout to a single-file layout, run the convert_diffusers_to_original_sdxl.py script. Provide the path to the model to convert, and the path to save the converted model to. You can optionally specify whether you want to save the model as a safetensors file and whether to save the model in half-precision.

python convert_diffusers_to_original_sdxl.py --model_path path/to/model/to/convert --checkpoint_path path/to/save/model/to --use_safetensors

I added ``` to end the block. Now it will display properly,

export_folder_as_dduf("flux-dev.dduf", folder_path=save_folder)
```

> [!TIP]

@stevhliu @sayakpaul

[stevhliu]

Nice, thanks for fixing!

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