diff --git a/examples/legacy/pytorch-lightning/run_ner.py b/examples/legacy/pytorch-lightning/run_ner.py
index 144759d36aac..6cbb138f023f 100644
--- a/examples/legacy/pytorch-lightning/run_ner.py
+++ b/examples/legacy/pytorch-lightning/run_ner.py
@@ -72,12 +72,12 @@ def prepare_data(self):
                     self.labels,
                     args.max_seq_length,
                     self.tokenizer,
-                    cls_token_at_end=bool(self.config.model_type in ["xlnet"]),
+                    cls_token_at_end=bool(self.config.model_type == "xlnet"),
                     cls_token=self.tokenizer.cls_token,
-                    cls_token_segment_id=2 if self.config.model_type in ["xlnet"] else 0,
+                    cls_token_segment_id=2 if self.config.model_type == "xlnet" else 0,
                     sep_token=self.tokenizer.sep_token,
                     sep_token_extra=False,
-                    pad_on_left=bool(self.config.model_type in ["xlnet"]),
+                    pad_on_left=bool(self.config.model_type == "xlnet"),
                     pad_token=self.tokenizer.pad_token_id,
                     pad_token_segment_id=self.tokenizer.pad_token_type_id,
                     pad_token_label_id=self.pad_token_label_id,
diff --git a/examples/legacy/token-classification/utils_ner.py b/examples/legacy/token-classification/utils_ner.py
index bfd792a250c3..b45a4fab40de 100644
--- a/examples/legacy/token-classification/utils_ner.py
+++ b/examples/legacy/token-classification/utils_ner.py
@@ -246,10 +246,10 @@ def __init__(
                         labels,
                         max_seq_length,
                         tokenizer,
-                        cls_token_at_end=bool(model_type in ["xlnet"]),
+                        cls_token_at_end=bool(model_type == "xlnet"),
                         # xlnet has a cls token at the end
                         cls_token=tokenizer.cls_token,
-                        cls_token_segment_id=2 if model_type in ["xlnet"] else 0,
+                        cls_token_segment_id=2 if model_type == "xlnet" else 0,
                         sep_token=tokenizer.sep_token,
                         sep_token_extra=False,
                         # roberta uses an extra separator b/w pairs of sentences, cf. github.com/pytorch/fairseq/commit/1684e166e3da03f5b600dbb7855cb98ddfcd0805
diff --git a/src/transformers/audio_utils.py b/src/transformers/audio_utils.py
index 231a78f38a0a..df4bbf1ca604 100644
--- a/src/transformers/audio_utils.py
+++ b/src/transformers/audio_utils.py
@@ -587,7 +587,7 @@ def window_function(
         window = np.hamming(length)
     elif name in ["hann", "hann_window"]:
         window = np.hanning(length)
-    elif name in ["povey"]:
+    elif name == "povey":
         window = np.power(np.hanning(length), 0.85)
     else:
         raise ValueError(f"Unknown window function '{name}'")
diff --git a/src/transformers/generation/utils.py b/src/transformers/generation/utils.py
index 156dca000176..97b98f96c202 100644
--- a/src/transformers/generation/utils.py
+++ b/src/transformers/generation/utils.py
@@ -883,7 +883,7 @@ def _prepare_decoder_input_ids_for_generation(
             self.config.model_type == "vision-encoder-decoder" and "donut" in self.config.encoder.model_type.lower()
         ):
             pass
-        elif self.config.model_type in ["whisper"]:
+        elif self.config.model_type == "whisper":
             pass
         # user input but doesn't start with decoder_start_token_id -> prepend decoder_start_token_id (and adjust
         # decoder_attention_mask if provided)
diff --git a/src/transformers/integrations/ggml.py b/src/transformers/integrations/ggml.py
index fd2c9c4e889a..d5600050188f 100644
--- a/src/transformers/integrations/ggml.py
+++ b/src/transformers/integrations/ggml.py
@@ -329,11 +329,11 @@ def _gguf_parse_value(_value, data_type):
         _value = int(_value[0])
     elif data_type in [6, 12]:
         _value = float(_value[0])
-    elif data_type in [7]:
+    elif data_type == 7:
         _value = bool(_value[0])
-    elif data_type in [8]:
+    elif data_type == 8:
         _value = array("B", list(_value)).tobytes().decode()
-    elif data_type in [9]:
+    elif data_type == 9:
         _value = _gguf_parse_value(_value, array_data_type)
     return _value
 
diff --git a/src/transformers/modeling_utils.py b/src/transformers/modeling_utils.py
index 7dcafa323a9c..d3e0f57a01c5 100644
--- a/src/transformers/modeling_utils.py
+++ b/src/transformers/modeling_utils.py
@@ -4001,7 +4001,7 @@ def save_pretrained(
                 if _is_dtensor_available and isinstance(state_dict[tensor], DTensor):
                     full_tensor = state_dict[tensor].full_tensor()
                     # to get the correctly ordered tensor we need to repack if packed
-                    if _get_parameter_tp_plan(tensor, self._tp_plan) in ("local_packed_rowwise",):
+                    if _get_parameter_tp_plan(tensor, self._tp_plan) == "local_packed_rowwise":
                         full_tensor = repack_weights(full_tensor, -1, self._tp_size, 2)
                     shard[tensor] = full_tensor.contiguous()  # only do contiguous after it's permuted correctly
                 else:
diff --git a/src/transformers/models/altclip/configuration_altclip.py b/src/transformers/models/altclip/configuration_altclip.py
index 5e8c0f2a262e..474fc48081b5 100755
--- a/src/transformers/models/altclip/configuration_altclip.py
+++ b/src/transformers/models/altclip/configuration_altclip.py
@@ -303,7 +303,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -335,7 +335,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/chinese_clip/configuration_chinese_clip.py b/src/transformers/models/chinese_clip/configuration_chinese_clip.py
index 5b9c31965585..776df308a898 100644
--- a/src/transformers/models/chinese_clip/configuration_chinese_clip.py
+++ b/src/transformers/models/chinese_clip/configuration_chinese_clip.py
@@ -306,7 +306,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -338,7 +338,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/clip/configuration_clip.py b/src/transformers/models/clip/configuration_clip.py
index 22c245485a0d..ae5c6bcaa8c3 100644
--- a/src/transformers/models/clip/configuration_clip.py
+++ b/src/transformers/models/clip/configuration_clip.py
@@ -295,7 +295,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -327,7 +327,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/clipseg/configuration_clipseg.py b/src/transformers/models/clipseg/configuration_clipseg.py
index 60b14eb7efbb..e338d278577a 100644
--- a/src/transformers/models/clipseg/configuration_clipseg.py
+++ b/src/transformers/models/clipseg/configuration_clipseg.py
@@ -307,7 +307,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -339,7 +339,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/dpt/modeling_dpt.py b/src/transformers/models/dpt/modeling_dpt.py
index d43279307aeb..4f9e7413bba6 100755
--- a/src/transformers/models/dpt/modeling_dpt.py
+++ b/src/transformers/models/dpt/modeling_dpt.py
@@ -864,7 +864,7 @@ def __init__(self, config: DPTConfig):
         self.config = config
 
         # postprocessing: only required in case of a non-hierarchical backbone (e.g. ViT, BEiT)
-        if config.backbone_config is not None and config.backbone_config.model_type in ["swinv2"]:
+        if config.backbone_config is not None and config.backbone_config.model_type == "swinv2":
             self.reassemble_stage = None
         else:
             self.reassemble_stage = DPTReassembleStage(config)
diff --git a/src/transformers/models/flava/configuration_flava.py b/src/transformers/models/flava/configuration_flava.py
index c3ecf68a8982..b7bcb920e47a 100644
--- a/src/transformers/models/flava/configuration_flava.py
+++ b/src/transformers/models/flava/configuration_flava.py
@@ -516,7 +516,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -548,7 +548,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_image_config_dict` and `image_config` but being different.
             for key, value in _image_config_dict.items():
-                if key in image_config and value != image_config[key] and key not in ["transformers_version"]:
+                if key in image_config and value != image_config[key] and key != "transformers_version":
                     # If specified in `image_config_dict`
                     if key in image_config_dict:
                         message = (
@@ -576,11 +576,7 @@ def __init__(
             # Give a warning if the values exist in both `_multimodal_config_dict` and `multimodal_config` but being
             # different.
             for key, value in _multimodal_config_dict.items():
-                if (
-                    key in multimodal_config
-                    and value != multimodal_config[key]
-                    and key not in ["transformers_version"]
-                ):
+                if key in multimodal_config and value != multimodal_config[key] and key != "transformers_version":
                     # If specified in `multimodal_config_dict`
                     if key in multimodal_config_dict:
                         message = (
@@ -611,7 +607,7 @@ def __init__(
                 if (
                     key in image_codebook_config
                     and value != image_codebook_config[key]
-                    and key not in ["transformers_version"]
+                    and key != "transformers_version"
                 ):
                     # If specified in `image_codebook_config_dict`
                     if key in image_codebook_config_dict:
diff --git a/src/transformers/models/groupvit/configuration_groupvit.py b/src/transformers/models/groupvit/configuration_groupvit.py
index cd9fb2d0469e..8366b3a08c0b 100644
--- a/src/transformers/models/groupvit/configuration_groupvit.py
+++ b/src/transformers/models/groupvit/configuration_groupvit.py
@@ -288,7 +288,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -320,7 +320,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/imagegpt/convert_imagegpt_original_tf2_to_pytorch.py b/src/transformers/models/imagegpt/convert_imagegpt_original_tf2_to_pytorch.py
index a1bb2efee2e1..445a83c82ee8 100644
--- a/src/transformers/models/imagegpt/convert_imagegpt_original_tf2_to_pytorch.py
+++ b/src/transformers/models/imagegpt/convert_imagegpt_original_tf2_to_pytorch.py
@@ -60,15 +60,18 @@ def load_tf_weights_in_imagegpt(model, config, imagegpt_checkpoint_path):
 
         # adam_v and adam_m are variables used in AdamWeightDecayOptimizer to calculated m and v
         # which are not required for using pretrained model
-        if any(
-            n in ["adam_v", "adam_m", "AdamWeightDecayOptimizer", "AdamWeightDecayOptimizer_1", "global_step"]
-            for n in name
-        ) or name[-1] in ["_step"]:
+        if (
+            any(
+                n in ["adam_v", "adam_m", "AdamWeightDecayOptimizer", "AdamWeightDecayOptimizer_1", "global_step"]
+                for n in name
+            )
+            or name[-1] == "_step"
+        ):
             logger.info("Skipping {}".format("/".join(name)))
             continue
 
         pointer = model
-        if name[-1] not in ["wtet"]:
+        if name[-1] != "wtet":
             pointer = getattr(pointer, "transformer")
 
         for m_name in name:
diff --git a/src/transformers/models/kosmos2_5/modeling_kosmos2_5.py b/src/transformers/models/kosmos2_5/modeling_kosmos2_5.py
index 4299e8ce7685..bcc4a87a62a5 100644
--- a/src/transformers/models/kosmos2_5/modeling_kosmos2_5.py
+++ b/src/transformers/models/kosmos2_5/modeling_kosmos2_5.py
@@ -273,9 +273,7 @@ class Kosmos2_5ModelOutput(ModelOutput):
     vision_model_output: BaseModelOutputWithPooling = None
 
     def to_tuple(self) -> tuple[Any]:
-        return tuple(
-            (self[k] if k not in ["vision_model_output"] else getattr(self, k).to_tuple()) for k in self.keys()
-        )
+        return tuple((self[k] if k != "vision_model_output" else getattr(self, k).to_tuple()) for k in self.keys())
 
 
 @dataclass
@@ -333,9 +331,7 @@ class Kosmos2_5ForConditionalGenerationModelOutput(ModelOutput):
     vision_model_output: BaseModelOutputWithPooling = None
 
     def to_tuple(self) -> tuple[Any]:
-        return tuple(
-            (self[k] if k not in ["vision_model_output"] else getattr(self, k).to_tuple()) for k in self.keys()
-        )
+        return tuple((self[k] if k != "vision_model_output" else getattr(self, k).to_tuple()) for k in self.keys())
 
 
 # Copied from transformers.models.pix2struct.modeling_pix2struct.Pix2StructLayerNorm with Pix2Struct->Kosmos2_5
diff --git a/src/transformers/models/llama/convert_llama_weights_to_hf.py b/src/transformers/models/llama/convert_llama_weights_to_hf.py
index 5267bfe9ba49..e63770a154de 100644
--- a/src/transformers/models/llama/convert_llama_weights_to_hf.py
+++ b/src/transformers/models/llama/convert_llama_weights_to_hf.py
@@ -398,7 +398,7 @@ def permute(w, n_heads, dim1=dim, dim2=dim):
             max_position_embeddings=max_position_embeddings,
             bos_token_id=bos_token_id,
             eos_token_id=eos_token_id,
-            tie_word_embeddings=llama_version in ["3.2"],
+            tie_word_embeddings=llama_version == "3.2",
         )
 
         config.save_pretrained(tmp_model_path)
@@ -451,7 +451,7 @@ def __init__(self, vocab_file, special_tokens=None, instruct=False, llama_versio
         # Prevents a null chat_template, which triggers
         # a parsing warning in the Hub.
         additional_kwargs = {}
-        if instruct or llama_version in ["Guard-3"]:
+        if instruct or llama_version == "Guard-3":
             model_id, revision = templates_for_version.get(llama_version, (None, None))
             if model_id is not None:
                 from transformers import AutoTokenizer
diff --git a/src/transformers/models/metaclip_2/configuration_metaclip_2.py b/src/transformers/models/metaclip_2/configuration_metaclip_2.py
index a0cec0f3c5b3..4ad1bcde0daa 100644
--- a/src/transformers/models/metaclip_2/configuration_metaclip_2.py
+++ b/src/transformers/models/metaclip_2/configuration_metaclip_2.py
@@ -277,7 +277,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -309,7 +309,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/perceiver/modeling_perceiver.py b/src/transformers/models/perceiver/modeling_perceiver.py
index 499d01774d06..ddab1d412c32 100755
--- a/src/transformers/models/perceiver/modeling_perceiver.py
+++ b/src/transformers/models/perceiver/modeling_perceiver.py
@@ -2804,7 +2804,7 @@ class PerceiverAudioPostprocessor(nn.Module):
     def __init__(self, config: PerceiverConfig, in_channels: int, postproc_type: str = "patches") -> None:
         super().__init__()
 
-        if postproc_type not in ("patches",):  # to be supported: 'conv', 'patches', 'pixels'
+        if postproc_type != "patches":  # to be supported: 'conv', 'patches', 'pixels'
             raise ValueError("Invalid postproc_type!")
 
         # Architecture parameters:
@@ -3137,7 +3137,7 @@ def __init__(
         super().__init__()
         self.config = config
 
-        if prep_type not in ("patches",):
+        if prep_type != "patches":
             raise ValueError(f"Prep_type {prep_type} is invalid, can only be 'patches'.")
 
         if concat_or_add_pos not in ["concat", "add"]:
diff --git a/src/transformers/models/phi3/configuration_phi3.py b/src/transformers/models/phi3/configuration_phi3.py
index a9009e837db5..33cee6b37ba5 100644
--- a/src/transformers/models/phi3/configuration_phi3.py
+++ b/src/transformers/models/phi3/configuration_phi3.py
@@ -210,7 +210,7 @@ def _rope_scaling_validation(self):
         rope_scaling_type = self.rope_scaling.get("type", None)
         rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
         rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
-        if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
+        if rope_scaling_type is None or rope_scaling_type != "longrope":
             raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
         if not (
             isinstance(rope_scaling_short_factor, list)
diff --git a/src/transformers/models/phi4_multimodal/configuration_phi4_multimodal.py b/src/transformers/models/phi4_multimodal/configuration_phi4_multimodal.py
index df9e09c481b0..e5e5ca91bfce 100644
--- a/src/transformers/models/phi4_multimodal/configuration_phi4_multimodal.py
+++ b/src/transformers/models/phi4_multimodal/configuration_phi4_multimodal.py
@@ -452,7 +452,7 @@ def _rope_scaling_validation(self):
         rope_scaling_type = self.rope_scaling.get("type", None)
         rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
         rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
-        if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
+        if rope_scaling_type is None or rope_scaling_type != "longrope":
             raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
         if not (
             isinstance(rope_scaling_short_factor, list)
diff --git a/src/transformers/models/qwen3_omni_moe/modeling_qwen3_omni_moe.py b/src/transformers/models/qwen3_omni_moe/modeling_qwen3_omni_moe.py
index 973b1624470b..a008c68d4fdc 100644
--- a/src/transformers/models/qwen3_omni_moe/modeling_qwen3_omni_moe.py
+++ b/src/transformers/models/qwen3_omni_moe/modeling_qwen3_omni_moe.py
@@ -3848,7 +3848,7 @@ def generate(
                     self.config.talker_config.text_config.vocab_size - 1024,
                     self.config.talker_config.text_config.vocab_size,
                 )
-                if i not in (self.config.talker_config.codec_eos_token_id,)
+                if i != self.config.talker_config.codec_eos_token_id
             ]  # Suppress additional special tokens, should not be predicted
             talker_kwargs = {
                 "max_new_tokens": talker_max_new_tokens,
diff --git a/src/transformers/models/qwen3_omni_moe/modular_qwen3_omni_moe.py b/src/transformers/models/qwen3_omni_moe/modular_qwen3_omni_moe.py
index 2dc964c28f5f..a7c147b42fb2 100644
--- a/src/transformers/models/qwen3_omni_moe/modular_qwen3_omni_moe.py
+++ b/src/transformers/models/qwen3_omni_moe/modular_qwen3_omni_moe.py
@@ -2425,7 +2425,7 @@ def generate(
                     self.config.talker_config.text_config.vocab_size - 1024,
                     self.config.talker_config.text_config.vocab_size,
                 )
-                if i not in (self.config.talker_config.codec_eos_token_id,)
+                if i != self.config.talker_config.codec_eos_token_id
             ]  # Suppress additional special tokens, should not be predicted
             talker_kwargs = {
                 "max_new_tokens": talker_max_new_tokens,
diff --git a/src/transformers/models/tapas/convert_tapas_original_tf_checkpoint_to_pytorch.py b/src/transformers/models/tapas/convert_tapas_original_tf_checkpoint_to_pytorch.py
index d9400b366e5f..d4a850cc2f4b 100644
--- a/src/transformers/models/tapas/convert_tapas_original_tf_checkpoint_to_pytorch.py
+++ b/src/transformers/models/tapas/convert_tapas_original_tf_checkpoint_to_pytorch.py
@@ -96,7 +96,7 @@ def load_tf_weights_in_tapas(model, config, tf_checkpoint_path):
                 continue
         # in case the model is TapasForMaskedLM, we skip the pooler
         if isinstance(model, TapasForMaskedLM):
-            if any(n in ["pooler"] for n in name):
+            if any(n == "pooler" for n in name):
                 logger.info(f"Skipping {'/'.join(name)}")
                 continue
         # if first scope name starts with "bert", change it to "tapas"
diff --git a/src/transformers/models/x_clip/configuration_x_clip.py b/src/transformers/models/x_clip/configuration_x_clip.py
index 66db819168e5..3fa6bb1544a8 100644
--- a/src/transformers/models/x_clip/configuration_x_clip.py
+++ b/src/transformers/models/x_clip/configuration_x_clip.py
@@ -294,7 +294,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -326,7 +326,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/zoedepth/modeling_zoedepth.py b/src/transformers/models/zoedepth/modeling_zoedepth.py
index f03804c2c57b..a88a444bf928 100644
--- a/src/transformers/models/zoedepth/modeling_zoedepth.py
+++ b/src/transformers/models/zoedepth/modeling_zoedepth.py
@@ -294,7 +294,7 @@ def __init__(self, config: ZoeDepthConfig):
         self.config = config
 
         # postprocessing: only required in case of a non-hierarchical backbone (e.g. ViT, BEiT)
-        if config.backbone_config is not None and config.backbone_config.model_type in ["swinv2"]:
+        if config.backbone_config is not None and config.backbone_config.model_type == "swinv2":
             self.reassemble_stage = None
         else:
             self.reassemble_stage = ZoeDepthReassembleStage(config)
diff --git a/src/transformers/pipelines/base.py b/src/transformers/pipelines/base.py
index 46ebf7172b73..9d6532508344 100644
--- a/src/transformers/pipelines/base.py
+++ b/src/transformers/pipelines/base.py
@@ -169,7 +169,7 @@ def inner(items):
         # input_values, input_pixels, input_ids, ...
         padded = {}
         for key in keys:
-            if key in {"input_ids"}:
+            if key == "input_ids":
                 # ImageGPT uses a feature extractor
                 if tokenizer is None and feature_extractor is not None:
                     _padding_value = f_padding_value
diff --git a/src/transformers/pipelines/text_generation.py b/src/transformers/pipelines/text_generation.py
index c77ca1d4bd37..e1ea152d7a0a 100644
--- a/src/transformers/pipelines/text_generation.py
+++ b/src/transformers/pipelines/text_generation.py
@@ -179,7 +179,7 @@ def _sanitize_parameters(
             generate_kwargs["prefix_length"] = prefix_inputs["input_ids"].shape[-1]
 
         if handle_long_generation is not None:
-            if handle_long_generation not in {"hole"}:
+            if handle_long_generation != "hole":
                 raise ValueError(
                     f"{handle_long_generation} is not a valid value for `handle_long_generation` parameter expected"
                     " [None, 'hole']"
@@ -234,7 +234,7 @@ def _parse_and_tokenize(self, *args, **kwargs):
         Parse arguments and tokenize
         """
         # Parse arguments
-        if self.model.__class__.__name__ in ["TransfoXLLMHeadModel"]:
+        if self.model.__class__.__name__ == "TransfoXLLMHeadModel":
             kwargs.update({"add_space_before_punct_symbol": True})
 
         return super()._parse_and_tokenize(*args, **kwargs)
diff --git a/src/transformers/testing_utils.py b/src/transformers/testing_utils.py
index c480014e7ff9..58b271934868 100644
--- a/src/transformers/testing_utils.py
+++ b/src/transformers/testing_utils.py
@@ -2779,7 +2779,7 @@ def wrapper(*args, **kwargs):
                             test = test.split("::")[1:]
                             command[idx] = "::".join([f"{func.__globals__['__file__']}"] + test)
                     command = [f"{sys.executable}", "-m", "pytest"] + command
-                    command = [x for x in command if x not in ["--no-summary"]]
+                    command = [x for x in command if x != "--no-summary"]
                 # Otherwise, simply run the test with no option at all
                 else:
                     command = [f"{sys.executable}", "-m", "pytest", f"{test}"]
@@ -4092,7 +4092,7 @@ def use_one_line_repr(obj):
                     if element_types[0] in [int, float]:
                         # one-line repr. without width limit
                         return no_new_line_in_elements
-                    elif element_types[0] in [str]:
+                    elif element_types[0] is str:
                         if len(obj) == 1:
                             # one single string element --> one-line repr. without width limit
                             return no_new_line_in_elements
diff --git a/src/transformers/utils/quantization_config.py b/src/transformers/utils/quantization_config.py
index 6c950bcbd298..82357e6f0fe2 100644
--- a/src/transformers/utils/quantization_config.py
+++ b/src/transformers/utils/quantization_config.py
@@ -1618,7 +1618,7 @@ def post_init(self):
             if self.hadamard_group_size not in [32, 64, 128]:
                 raise ValueError("Only a `hadamard_group_size` of [32, 64, 128] is supported for 'mxfp4'.")
         elif self.forward_dtype == "nvfp4":
-            if self.forward_method not in ["abs_max"]:
+            if self.forward_method != "abs_max":
                 raise ValueError("Only 'abs_max' is supported for forward_method for 'nvfp4'.")
             if self.hadamard_group_size is None:
                 self.hadamard_group_size = 16
@@ -1627,7 +1627,7 @@ def post_init(self):
         else:
             raise ValueError("Only 'mxfp4' and 'nvfp4' are supported for forward_dtype for now.")
 
-        if self.backward_dtype not in ["bf16"]:
+        if self.backward_dtype != "bf16":
             raise ValueError("Only 'bf16' is supported for backward_dtype for now.")
         if self.transform_init not in ["hadamard", "identity", "gsr"]:
             raise ValueError("Only 'hadamard', 'identity' and 'gsr' are supported for transform_init.")
@@ -2026,7 +2026,7 @@ def post_init(self):
         Safety checker that arguments are correct
         """
         self.activation_scheme = self.activation_scheme.lower()
-        if self.activation_scheme not in ["dynamic"]:
+        if self.activation_scheme != "dynamic":
             raise ValueError(f"Activation scheme {self.activation_scheme} not supported")
         if len(self.weight_block_size) != 2:
             raise ValueError("weight_block_size must be a tuple of two integers")
diff --git a/src/transformers/video_utils.py b/src/transformers/video_utils.py
index 253113c1fd44..73aebbfcbf26 100644
--- a/src/transformers/video_utils.py
+++ b/src/transformers/video_utils.py
@@ -694,7 +694,7 @@ def sample_indices_fn_func(metadata, **fn_kwargs):
     # can also load with decord, but not cv2/torchvision
     # both will fail in case of url links
     video_is_url = video.startswith("http://") or video.startswith("https://")
-    if video_is_url and backend in ["opencv"]:
+    if video_is_url and backend == "opencv":
         raise ValueError("If you are trying to load a video from URL, you cannot use 'opencv' as backend")
 
     if (
diff --git a/tests/models/autoformer/test_modeling_autoformer.py b/tests/models/autoformer/test_modeling_autoformer.py
index 6f25b1865351..c721029f0a49 100644
--- a/tests/models/autoformer/test_modeling_autoformer.py
+++ b/tests/models/autoformer/test_modeling_autoformer.py
@@ -287,7 +287,7 @@ def test_forward_signature(self):
                 "future_time_features",
             ]
 
-            if model.__class__.__name__ in ["AutoformerForPrediction"]:
+            if model.__class__.__name__ == "AutoformerForPrediction":
                 expected_arg_names.append("future_observed_mask")
 
             expected_arg_names.extend(
diff --git a/tests/models/bros/test_modeling_bros.py b/tests/models/bros/test_modeling_bros.py
index 8f3f5957e02e..681c1e98bdd8 100644
--- a/tests/models/bros/test_modeling_bros.py
+++ b/tests/models/bros/test_modeling_bros.py
@@ -323,7 +323,7 @@ def _prepare_for_class(self, inputs_dict, model_class, return_labels=False):
                     dtype=torch.bool,
                     device=torch_device,
                 )
-            elif model_class.__name__ in ["BrosSpadeEEForTokenClassification"]:
+            elif model_class.__name__ == "BrosSpadeEEForTokenClassification":
                 inputs_dict["initial_token_labels"] = torch.zeros(
                     (self.model_tester.batch_size, self.model_tester.seq_length),
                     dtype=torch.long,
diff --git a/tests/models/dab_detr/test_modeling_dab_detr.py b/tests/models/dab_detr/test_modeling_dab_detr.py
index 93ee29b0d126..f9446e2eaee2 100644
--- a/tests/models/dab_detr/test_modeling_dab_detr.py
+++ b/tests/models/dab_detr/test_modeling_dab_detr.py
@@ -193,7 +193,7 @@ def _prepare_for_class(self, inputs_dict, model_class, return_labels=False):
         inputs_dict = super()._prepare_for_class(inputs_dict, model_class, return_labels=return_labels)
 
         if return_labels:
-            if model_class.__name__ in ["DabDetrForObjectDetection"]:
+            if model_class.__name__ == "DabDetrForObjectDetection":
                 labels = []
                 for i in range(self.model_tester.batch_size):
                     target = {}
diff --git a/tests/models/mask2former/test_image_processing_mask2former.py b/tests/models/mask2former/test_image_processing_mask2former.py
index 439a111db8f2..8ece9b9eebc7 100644
--- a/tests/models/mask2former/test_image_processing_mask2former.py
+++ b/tests/models/mask2former/test_image_processing_mask2former.py
@@ -549,7 +549,7 @@ def test_post_process_label_fusing(self):
                     continue
 
                 # Get number of segments to be fused
-                fuse_targets = [1 for el in el_unfused if el["label_id"] in {1}]
+                fuse_targets = [1 for el in el_unfused if el["label_id"] == 1]
                 num_to_fuse = 0 if len(fuse_targets) == 0 else sum(fuse_targets) - 1
                 # Expected number of segments after fusing
                 expected_num_segments = max([el["id"] for el in el_unfused]) - num_to_fuse
diff --git a/tests/models/maskformer/test_image_processing_maskformer.py b/tests/models/maskformer/test_image_processing_maskformer.py
index 44797837233c..d0f0a0875092 100644
--- a/tests/models/maskformer/test_image_processing_maskformer.py
+++ b/tests/models/maskformer/test_image_processing_maskformer.py
@@ -537,7 +537,7 @@ def test_post_process_label_fusing(self):
                     continue
 
                 # Get number of segments to be fused
-                fuse_targets = [1 for el in el_unfused if el["label_id"] in {1}]
+                fuse_targets = [1 for el in el_unfused if el["label_id"] == 1]
                 num_to_fuse = 0 if len(fuse_targets) == 0 else sum(fuse_targets) - 1
                 # Expected number of segments after fusing
                 expected_num_segments = max([el["id"] for el in el_unfused]) - num_to_fuse
diff --git a/tests/models/maskformer/test_modeling_maskformer.py b/tests/models/maskformer/test_modeling_maskformer.py
index 42e565a9e16a..aea9bc0d0ead 100644
--- a/tests/models/maskformer/test_modeling_maskformer.py
+++ b/tests/models/maskformer/test_modeling_maskformer.py
@@ -218,7 +218,7 @@ def _prepare_for_class(self, inputs_dict, model_class, return_labels=False):
         inputs_dict = copy.deepcopy(inputs_dict)
 
         if return_labels:
-            if model_class in [MaskFormerForInstanceSegmentation]:
+            if model_class == MaskFormerForInstanceSegmentation:
                 inputs_dict["mask_labels"] = torch.zeros(
                     (
                         self.model_tester.batch_size,
diff --git a/tests/models/modernbert_decoder/test_modeling_modernbert_decoder.py b/tests/models/modernbert_decoder/test_modeling_modernbert_decoder.py
index 41371a75aa76..fcfb8f28e796 100644
--- a/tests/models/modernbert_decoder/test_modeling_modernbert_decoder.py
+++ b/tests/models/modernbert_decoder/test_modeling_modernbert_decoder.py
@@ -63,7 +63,7 @@ def test_initialization(self):
                 # The classifier.weight from ModernBertDecoderForSequenceClassification
                 # is initialized without `initializer_range`, so it's not set to ~0 via the _config_zero_init
                 if param.requires_grad and not (
-                    name == "classifier.weight" and model_class in [ModernBertDecoderForSequenceClassification]
+                    name == "classifier.weight" and model_class == ModernBertDecoderForSequenceClassification
                 ):
                     data = torch.flatten(param.data)
                     n_elements = torch.numel(data)
diff --git a/tests/models/musicgen/test_modeling_musicgen.py b/tests/models/musicgen/test_modeling_musicgen.py
index 25726fabeecd..e5b876b42604 100644
--- a/tests/models/musicgen/test_modeling_musicgen.py
+++ b/tests/models/musicgen/test_modeling_musicgen.py
@@ -965,7 +965,7 @@ def test_sdpa_can_dispatch_on_flash(self):
                 self.skipTest(
                     reason="Llava-like models currently (transformers==4.39.1) requires an attention_mask input"
                 )
-            if config.model_type in ["paligemma"]:
+            if config.model_type == "paligemma":
                 self.skipTest(
                     "PaliGemma-like models currently (transformers==4.41.0) requires an attention_mask input"
                 )
diff --git a/tests/models/musicgen_melody/test_modeling_musicgen_melody.py b/tests/models/musicgen_melody/test_modeling_musicgen_melody.py
index 8700e06388a7..4d487546c741 100644
--- a/tests/models/musicgen_melody/test_modeling_musicgen_melody.py
+++ b/tests/models/musicgen_melody/test_modeling_musicgen_melody.py
@@ -968,7 +968,7 @@ def test_sdpa_can_dispatch_on_flash(self):
                 self.skipTest(
                     reason="Llava-like models currently (transformers==4.39.1) requires an attention_mask input"
                 )
-            if config.model_type in ["paligemma"]:
+            if config.model_type == "paligemma":
                 self.skipTest(
                     "PaliGemma-like models currently (transformers==4.41.0) requires an attention_mask input"
                 )
diff --git a/tests/models/table_transformer/test_modeling_table_transformer.py b/tests/models/table_transformer/test_modeling_table_transformer.py
index a9d7d4772961..460f41495d73 100644
--- a/tests/models/table_transformer/test_modeling_table_transformer.py
+++ b/tests/models/table_transformer/test_modeling_table_transformer.py
@@ -213,7 +213,7 @@ def _prepare_for_class(self, inputs_dict, model_class, return_labels=False):
         inputs_dict = super()._prepare_for_class(inputs_dict, model_class, return_labels=return_labels)
 
         if return_labels:
-            if model_class.__name__ in ["TableTransformerForObjectDetection"]:
+            if model_class.__name__ == "TableTransformerForObjectDetection":
                 labels = []
                 for i in range(self.model_tester.batch_size):
                     target = {}
diff --git a/tests/test_modeling_common.py b/tests/test_modeling_common.py
index 81a93dd89c29..15d221e7a48d 100755
--- a/tests/test_modeling_common.py
+++ b/tests/test_modeling_common.py
@@ -2793,7 +2793,7 @@ def check_device_map_is_respected(self, model, device_map):
             param_device = device_map[param_name]
             if param_device in ["cpu", "disk"]:
                 self.assertEqual(param.device, torch.device("meta"))
-            elif param_device in ["mps"]:
+            elif param_device == "mps":
                 self.assertEqual(param.device, torch.device("mps"))
             else:
                 # when loaded with device_map, `param_device` are integer values for cuda/xpu/hpu/npu/mlu
@@ -3532,7 +3532,7 @@ def test_sdpa_can_dispatch_on_flash(self):
 
             config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
             inputs_dict = self._prepare_for_class(inputs_dict, model_class)
-            if config.model_type in ["paligemma"]:
+            if config.model_type == "paligemma":
                 self.skipTest(
                     "PaliGemma-like models currently (transformers==4.41.0) requires an attention_mask input"
                 )
@@ -3560,7 +3560,7 @@ def test_sdpa_can_dispatch_on_flash(self):
                 )
             if config.model_type in ["idefics", "idefics2", "idefics3"]:
                 self.skipTest(reason="Idefics currently (transformers==4.39.1) requires an image_attention_mask input")
-            if config.model_type in ["sam"]:
+            if config.model_type == "sam":
                 self.skipTest(reason="SAM requires an attention_mask input for relative positional embeddings")
 
             model = model_class(config)
@@ -3614,7 +3614,7 @@ def test_sdpa_can_compile_dynamic(self):
 
             config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
             inputs_dict = self._prepare_for_class(inputs_dict, model_class)
-            if config.model_type in ["dbrx"]:
+            if config.model_type == "dbrx":
                 self.skipTest(
                     "DBRX (transformers==4.40) requires a modification to support dynamic shapes with compile."
                 )
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index 9a80f0032e7a..3c69b1d20cb7 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -1764,7 +1764,7 @@ def is_any_loss_nan_or_inf(log_history):
         self.assertFalse(is_any_loss_nan_or_inf(log_history_filter))
 
     def test_train_and_eval_dataloaders(self):
-        if torch_device in ["cuda"]:
+        if torch_device == "cuda":
             n_gpu = max(1, backend_device_count(torch_device))
         else:
             # DP is deprecated by PyTorch, accelerators like XPU doesn't support DP
diff --git a/utils/check_config_attributes.py b/utils/check_config_attributes.py
index 29fa59987266..7b7c3bd4502a 100644
--- a/utils/check_config_attributes.py
+++ b/utils/check_config_attributes.py
@@ -435,9 +435,9 @@ def check_attribute_being_used(config_class, attributes, default_value, source_s
         case_allowed = False
         for attribute in attributes:
             # Allow if the default value in the configuration class is different from the one in `PretrainedConfig`
-            if attribute in ["is_encoder_decoder"] and default_value is True:
+            if attribute == "is_encoder_decoder" and default_value is True:
                 case_allowed = True
-            elif attribute in ["tie_word_embeddings"] and default_value is False:
+            elif attribute == "tie_word_embeddings" and default_value is False:
                 case_allowed = True
 
             # Allow cases without checking the default value in the configuration class
diff --git a/utils/check_model_tester.py b/utils/check_model_tester.py
index 60f7c0d32c3d..57fd337fb7a7 100644
--- a/utils/check_model_tester.py
+++ b/utils/check_model_tester.py
@@ -40,9 +40,9 @@
                 for k, v in config.to_dict().items():
                     if isinstance(v, int):
                         target = None
-                        if k in ["vocab_size"]:
+                        if k == "vocab_size":
                             target = 100
-                        elif k in ["max_position_embeddings"]:
+                        elif k == "max_position_embeddings":
                             target = 128
                         elif k in ["hidden_size", "d_model"]:
                             target = 40
diff --git a/utils/tests_fetcher.py b/utils/tests_fetcher.py
index 49821d703890..de0b8d52258c 100644
--- a/utils/tests_fetcher.py
+++ b/utils/tests_fetcher.py
@@ -409,7 +409,7 @@ def get_diff_for_doctesting(repo: Repo, base_commit: str, commits: list[str]) ->
             if not diff_obj.b_path.endswith(".py") and not diff_obj.b_path.endswith(".md"):
                 continue
             # We always add new python/md files
-            if diff_obj.change_type in ["A"]:
+            if diff_obj.change_type == "A":
                 code_diff.append(diff_obj.b_path)
             # Now for modified files
             elif diff_obj.change_type in ["M", "R"]: