Add sampling_settings so models can specify specific sampling settings.

comfy/model_sampling.py

@@ -24,7 +24,7 @@ class ModelSamplingDiscrete(torch.nn.Module):
         super().__init__()
         beta_schedule = "linear"
         if model_config is not None:
-            beta_schedule = model_config.beta_schedule
+            beta_schedule = model_config.sampling_settings.get("beta_schedule", beta_schedule)
         self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=1000, linear_start=0.00085, linear_end=0.012, cosine_s=8e-3)
         self.sigma_data = 1.0
 

comfy/supported_models_base.py

@@ -19,7 +19,7 @@ class BASE:
     clip_prefix = []
     clip_vision_prefix = None
     noise_aug_config = None
-    beta_schedule = "linear"
+    sampling_settings = {}
     latent_format = latent_formats.LatentFormat
 
     @classmethod