feat: add performance hyper-sd based on 4step LoRA (#2812)

* feat: add performance hyper-sd based on 4step LoRA

* feat: use LoRA weight 0.8, sampler dpmpp_sde_gpu and scheduler_name karras

suggested in https://github.com/lllyasviel/Fooocus/discussions/2813#discussioncomment-9245251
results see https://github.com/lllyasviel/Fooocus/discussions/2813#discussioncomment-9275251

* feat: change ByteDance huggingface profile with mashb1t

* wip: add hyper-sd 8 step cfg lora with negative prompt support

* feat: remove hyper-sd8 performance

still waiting for the release of hyper-sd 4step CFG LoRA, not yet satisfied with any of the CFG LoRAs compared to non-cfg ones.
see https://huggingface.co/ByteDance/Hyper-SD

modules/flags.py

@@ -110,6 +110,7 @@ class Steps(IntEnum):
     SPEED = 30
     EXTREME_SPEED = 8
     LIGHTNING = 4
+    HYPER_SD = 4
 
 
 class StepsUOV(IntEnum):
@@ -117,6 +118,7 @@ class StepsUOV(IntEnum):
     SPEED = 18
     EXTREME_SPEED = 8
     LIGHTNING = 4
+    HYPER_SD = 4
 
 
 class Performance(Enum):
@@ -124,6 +126,7 @@ class Performance(Enum):
     SPEED = 'Speed'
     EXTREME_SPEED = 'Extreme Speed'
     LIGHTNING = 'Lightning'
+    HYPER_SD = 'Hyper-SD'
 
     @classmethod
     def list(cls) -> list:
@@ -133,7 +136,7 @@ class Performance(Enum):
     def has_restricted_features(cls, x) -> bool:
         if isinstance(x, Performance):
             x = x.value
-        return x in [cls.EXTREME_SPEED.value, cls.LIGHTNING.value]
+        return x in [cls.EXTREME_SPEED.value, cls.LIGHTNING.value, cls.HYPER_SD.value]
 
     def steps(self) -> int | None:
         return Steps[self.name].value if Steps[self.name] else None