diff --git a/modules/exllamav2.py b/modules/exllamav2.py
index 5d5c5b56..3b3233d2 100644
--- a/modules/exllamav2.py
+++ b/modules/exllamav2.py
@@ -3,6 +3,7 @@ import traceback
 from pathlib import Path
 
 import torch
+
 from exllamav2 import (
     ExLlamaV2,
     ExLlamaV2Cache,
@@ -15,7 +16,6 @@ from exllamav2 import (
     ExLlamaV2Tokenizer
 )
 from exllamav2.generator import ExLlamaV2Sampler, ExLlamaV2StreamingGenerator
-
 from modules import shared
 from modules.logging_colors import logger
 from modules.text_generation import get_max_prompt_length
diff --git a/modules/exllamav3.py b/modules/exllamav3.py
index 3fabdb6b..980230f8 100644
--- a/modules/exllamav3.py
+++ b/modules/exllamav3.py
@@ -2,12 +2,9 @@ import traceback
 from pathlib import Path
 from typing import Any, List, Tuple
 
-import torch
 from exllamav3 import Cache, Config, Generator, Model, Tokenizer
 from exllamav3.cache import CacheLayer_fp16, CacheLayer_quant
 from exllamav3.generator import Job
-
-from modules import shared
 from exllamav3.generator.sampler import (
     CustomSampler,
     SS_Argmax,
@@ -19,13 +16,13 @@ from exllamav3.generator.sampler import (
     SS_TopK,
     SS_TopP
 )
+from modules import shared
 from modules.image_utils import (
     convert_image_attachments_to_pil,
     convert_openai_messages_to_images
 )
 from modules.logging_colors import logger
 from modules.text_generation import get_max_prompt_length
-from modules.torch_utils import clear_torch_cache
 
 try:
     import flash_attn
@@ -205,13 +202,13 @@ class Exllamav3Model:
             penalty_range = state['repetition_penalty_range']
             if penalty_range <= 0:
                 penalty_range = int(10e7)  # Use large number for "full context"
-            rep_decay = 0 # Not a configurable parameter
+            rep_decay = 0  # Not a configurable parameter
 
             # Add penalty samplers if they are active
             if state['repetition_penalty'] != 1.0:
-                 unordered_samplers.append(SS_RepP(state['repetition_penalty'], penalty_range, rep_decay))
+                unordered_samplers.append(SS_RepP(state['repetition_penalty'], penalty_range, rep_decay))
             if state['presence_penalty'] != 0.0 or state['frequency_penalty'] != 0.0:
-                 unordered_samplers.append(SS_PresFreqP(state['presence_penalty'], state['frequency_penalty'], penalty_range, rep_decay))
+                unordered_samplers.append(SS_PresFreqP(state['presence_penalty'], state['frequency_penalty'], penalty_range, rep_decay))
 
             # Standard samplers
             if state['top_k'] > 0: