Change step_offset scheduler docstrings (#7128)

* Change step_offset scheduler docstrings

* Mention it may be needed by some models

* More docstrings

These ones failed literal S&R because I performed it case-sensitive
which is fun.

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

src/diffusers/schedulers/scheduling_pndm.py

@@ -104,9 +104,7 @@ class PNDMScheduler(SchedulerMixin, ConfigMixin):
             The way the timesteps should be scaled. Refer to Table 2 of the [Common Diffusion Noise Schedules and
             Sample Steps are Flawed](https://huggingface.co/papers/2305.08891) for more information.
         steps_offset (`int`, defaults to 0):
-            An offset added to the inference steps. You can use a combination of `offset=1` and
-            `set_alpha_to_one=False` to make the last step use step 0 for the previous alpha product like in Stable
-            Diffusion.
+            An offset added to the inference steps, as required by some model families.
     """
 
     _compatibles = [e.name for e in KarrasDiffusionSchedulers]

src/diffusers/schedulers/scheduling_pndm_flax.py

@@ -99,9 +99,7 @@ class FlaxPNDMScheduler(FlaxSchedulerMixin, ConfigMixin):
             step there is no previous alpha. When this option is `True` the previous alpha product is fixed to `1`,
             otherwise it uses the value of alpha at step 0.
         steps_offset (`int`, default `0`):
-            an offset added to the inference steps. You can use a combination of `offset=1` and
-            `set_alpha_to_one=False`, to make the last step use step 0 for the previous alpha product, as done in
-            stable diffusion.
+            An offset added to the inference steps, as required by some model families.
         prediction_type (`str`, default `epsilon`, optional):
             prediction type of the scheduler function, one of `epsilon` (predicting the noise of the diffusion
             process), `sample` (directly predicting the noisy sample`) or `v_prediction` (see section 2.4

src/diffusers/schedulers/scheduling_sasolver.py

@@ -131,9 +131,7 @@ class SASolverScheduler(SchedulerMixin, ConfigMixin):
             The way the timesteps should be scaled. Refer to Table 2 of the [Common Diffusion Noise Schedules and
             Sample Steps are Flawed](https://huggingface.co/papers/2305.08891) for more information.
         steps_offset (`int`, defaults to 0):
-            An offset added to the inference steps. You can use a combination of `offset=1` and
-            `set_alpha_to_one=False` to make the last step use step 0 for the previous alpha product like in Stable
-            Diffusion.
+            An offset added to the inference steps, as required by some model families.
     """
 
     _compatibles = [e.name for e in KarrasDiffusionSchedulers]

src/diffusers/schedulers/scheduling_tcd.py

@@ -166,9 +166,7 @@ class TCDScheduler(SchedulerMixin, ConfigMixin):
             there is no previous alpha. When this option is `True` the previous alpha product is fixed to `1`,
             otherwise it uses the alpha value at step 0.
         steps_offset (`int`, defaults to 0):
-            An offset added to the inference steps. You can use a combination of `offset=1` and
-            `set_alpha_to_one=False` to make the last step use step 0 for the previous alpha product like in Stable
-            Diffusion.
+            An offset added to the inference steps, as required by some model families.
         prediction_type (`str`, defaults to `epsilon`, *optional*):
             Prediction type of the scheduler function; can be `epsilon` (predicts the noise of the diffusion process),
             `sample` (directly predicts the noisy sample`) or `v_prediction` (see section 2.4 of [Imagen

src/diffusers/schedulers/scheduling_unipc_multistep.py

@@ -126,9 +126,7 @@ class UniPCMultistepScheduler(SchedulerMixin, ConfigMixin):
             The way the timesteps should be scaled. Refer to Table 2 of the [Common Diffusion Noise Schedules and
             Sample Steps are Flawed](https://huggingface.co/papers/2305.08891) for more information.
         steps_offset (`int`, defaults to 0):
-            An offset added to the inference steps. You can use a combination of `offset=1` and
-            `set_alpha_to_one=False` to make the last step use step 0 for the previous alpha product like in Stable
-            Diffusion.
+            An offset added to the inference steps, as required by some model families.
     """
 
     _compatibles = [e.name for e in KarrasDiffusionSchedulers]