[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

unsloth/kernels/fp8.py

@@ -532,23 +532,26 @@ def test_has_fbgemm():
     block_scale = torch.ones(M // 128, K // 128, dtype = torch.float32, device = "cuda")
     has_fbgemm = False
     try:
-        out = torch.ops.fbgemm.f8f8bf16_blockwise(
-            xq, wq, block_scale, block_scale
-        )
+        out = torch.ops.fbgemm.f8f8bf16_blockwise(xq, wq, block_scale, block_scale)
         assert torch.unique(out).item() == 128
         has_fbgemm = True
         del out
     except Exception as e:
         e = str(e)
         if "cutlass cannot initialize" in e.lower():
-            print(f"Unsloth: FBGEMM on the current GPU cannot load - will switch to Triton kernels")
+            print(
+                f"Unsloth: FBGEMM on the current GPU cannot load - will switch to Triton kernels"
+            )
         else:
-            print(f"Unsloth: FBGEMM on the current GPU cannot load with error = {e} - will switch to Triton kernels")
+            print(
+                f"Unsloth: FBGEMM on the current GPU cannot load with error = {e} - will switch to Triton kernels"
+            )
         has_fbgemm = False
     del block_scale, xq
     torch.cuda.empty_cache()
     return has_fbgemm
 
+
 fp8_block_quant_linear = fp8_torch_block_quant_forward
 if "UNSLOTH_HAS_FBGEMM" not in os.environ:
     os.environ["UNSLOTH_HAS_FBGEMM"] = "0"

unsloth/models/loader.py

@@ -223,7 +223,9 @@ class FastLanguageModel(FastLlamaModel):
         old_model_name = model_name
         fp8_mode = None
         if not use_exact_model_name:
-            new_model_name = get_model_name(model_name, load_in_4bit = load_in_4bit, load_in_fp8 = load_in_fp8)
+            new_model_name = get_model_name(
+                model_name, load_in_4bit = load_in_4bit, load_in_fp8 = load_in_fp8
+            )
             if new_model_name is None and load_in_fp8 != False:
                 fp8_mode = _get_fp8_mode_and_check_settings(
                     load_in_fp8,
@@ -378,7 +380,7 @@ class FastLanguageModel(FastLlamaModel):
             if model_name.lower().endswith("-bf16"):
                 load_in_4bit = False
                 load_in_8bit = False
-                load_in_fp8  = False
+                load_in_fp8 = False
                 load_in_16bit = True
 
             model_config = AutoConfig.from_pretrained(
@@ -730,7 +732,9 @@ class FastModel(FastBaseModel):
         old_model_name = model_name
         fp8_mode = None
         if not use_exact_model_name:
-            new_model_name = get_model_name(model_name, load_in_4bit = load_in_4bit, load_in_fp8 = load_in_fp8)
+            new_model_name = get_model_name(
+                model_name, load_in_4bit = load_in_4bit, load_in_fp8 = load_in_fp8
+            )
             if new_model_name is None and load_in_fp8 != False:
                 fp8_mode = _get_fp8_mode_and_check_settings(
                     load_in_fp8,
@@ -757,7 +761,7 @@ class FastModel(FastBaseModel):
         if model_name.lower().endswith("-bf16"):
             load_in_4bit = False
             load_in_8bit = False
-            load_in_fp8  = False
+            load_in_fp8 = False
             load_in_16bit = True
 
         # Check modelscope
@@ -1018,7 +1022,7 @@ class FastModel(FastBaseModel):
             if model_name.lower().endswith("-bf16"):
                 load_in_4bit = False
                 load_in_8bit = False
-                load_in_fp8  = False
+                load_in_fp8 = False
                 load_in_16bit = True
 
             model_config = AutoConfig.from_pretrained(

unsloth/models/loader_utils.py

@@ -242,6 +242,7 @@ def _offline_quantize_to_fp8(model_name: str, fp8_mode: str) -> str:
             TorchAoConfig,
             AutoConfig,
         )
+
         qconfig = _get_torchao_fp8_config(fp8_mode)
         qconfig = TorchAoConfig(qconfig)
         config = AutoConfig.from_pretrained(model_name)
@@ -334,11 +335,15 @@ def _get_fp8_mode_and_check_settings(
         and torch.version.cuda
         and torch.cuda.get_device_capability() >= (9, 0)
     ):
-        raise ValueError("Unsloth: On the fly `load_in_fp8` requires H100 GPUs or after. Try `unsloth/Qwen3-8B` instead.")
+        raise ValueError(
+            "Unsloth: On the fly `load_in_fp8` requires H100 GPUs or after. Try `unsloth/Qwen3-8B` instead."
+        )
 
     # Check if torch >= 2.9.0
     if Version(torch.__version__) < Version("2.9.0"):
-        raise ValueError("Unsloth: On the fly `load_in_fp8` requires torch 2.9.0+. Try `unsloth/Qwen3-8B` instead.")
+        raise ValueError(
+            "Unsloth: On the fly `load_in_fp8` requires torch 2.9.0+. Try `unsloth/Qwen3-8B` instead."
+        )
 
     # Check if torchao has this PR: https://github.com/pytorch/ao/pull/3158,
     # which will be released in 0.15.0.

unsloth/models/mapper.py

@@ -1281,7 +1281,6 @@ for key, values in __INT_TO_FLOAT_MAPPER.items():
             for k in float8_values:
                 FLOAT_TO_FP8_BLOCK_MAPPER[k.lower()] = block
                 FLOAT_TO_FP8_ROW_MAPPER[k.lower()] = row
-        pass
         values = float16_values
     INT_TO_FLOAT_MAPPER[key] = values[0]