Bugfix/remove emojis from print

examples/pytorch/language-modeling/run_clm_no_trainer.py

@@ -127,7 +127,7 @@ def parse_args():
     parser.add_argument(
         "--use_slow_tokenizer",
         action="store_true",
-        help="If passed, will use a slow tokenizer (not backed by the 🤗 Tokenizers library).",
+        help="If passed, will use a slow tokenizer (not backed by the Hugging Face Tokenizers library).",
     )
     parser.add_argument(
         "--per_device_train_batch_size",

examples/pytorch/language-modeling/run_fim_no_trainer.py

@@ -132,7 +132,7 @@ def parse_args():
     parser.add_argument(
         "--use_slow_tokenizer",
         action="store_true",
-        help="If passed, will use a slow tokenizer (not backed by the 🤗 Tokenizers library).",
+        help="If passed, will use a slow tokenizer (not backed by the Tokenizers library).",
     )
     parser.add_argument(
         "--per_device_train_batch_size",

examples/pytorch/language-modeling/run_mlm_no_trainer.py

@@ -130,7 +130,7 @@ def parse_args():
     parser.add_argument(
         "--use_slow_tokenizer",
         action="store_true",
-        help="If passed, will use a slow tokenizer (not backed by the 🤗 Tokenizers library).",
+        help="If passed, will use a slow tokenizer (not backed by the Hugging Face Tokenizers library).",
     )
     parser.add_argument(
         "--per_device_train_batch_size",

examples/pytorch/multiple-choice/run_swag_no_trainer.py

@@ -128,7 +128,7 @@ def parse_args():
     parser.add_argument(
         "--use_slow_tokenizer",
         action="store_true",
-        help="If passed, will use a slow tokenizer (not backed by the 🤗 Tokenizers library).",
+        help="If passed, will use a slow tokenizer (not backed by the HuggingFace Tokenizers library).",
     )
     parser.add_argument(
         "--per_device_train_batch_size",

examples/pytorch/question-answering/run_qa_no_trainer.py

@@ -151,7 +151,7 @@ def parse_args():
     parser.add_argument(
         "--use_slow_tokenizer",
         action="store_true",
-        help="If passed, will use a slow tokenizer (not backed by the 🤗 Tokenizers library).",
+        help="If passed, will use a slow tokenizer (not backed by the Hugging Face Tokenizers library).",
     )
     parser.add_argument(
         "--per_device_train_batch_size",

examples/pytorch/summarization/run_summarization_no_trainer.py

@@ -223,7 +223,7 @@ def parse_args():
     parser.add_argument(
         "--use_slow_tokenizer",
         action="store_true",
-        help="If passed, will use a slow tokenizer (not backed by the 🤗 Tokenizers library).",
+        help="If passed, will use a slow tokenizer (not backed by the Hugging Face Tokenizers library).",
     )
     parser.add_argument(
         "--per_device_train_batch_size",

examples/pytorch/text-classification/run_glue_no_trainer.py

@@ -120,7 +120,7 @@ def parse_args():
     parser.add_argument(
         "--use_slow_tokenizer",
         action="store_true",
-        help="If passed, will use a slow tokenizer (not backed by the 🤗 Tokenizers library).",
+        help="If passed, will use a slow tokenizer (not backed by the Hugging Face Tokenizers library).",
     )
     parser.add_argument(
         "--per_device_train_batch_size",

examples/pytorch/translation/run_translation_no_trainer.py

@@ -212,7 +212,7 @@ def parse_args():
     parser.add_argument(
         "--use_slow_tokenizer",
         action="store_true",
-        help="If passed, will use a slow tokenizer (not backed by the 🤗 Tokenizers library).",
+        help="If passed, will use a slow tokenizer (not backed by the Hugging Face Tokenizers library).",
     )
     parser.add_argument(
         "--per_device_train_batch_size",

src/transformers/data/datasets/glue.py

@@ -82,7 +82,7 @@ def __init__(
         cache_dir: Optional[str] = None,
     ):
         warnings.warn(
-            "This dataset will be removed from the library soon, preprocessing should be handled with the 🤗 Datasets "
+            "This dataset will be removed from the library soon, preprocessing should be handled with the Hugging Face Datasets "
             "library. You can have a look at this example script for pointers: "
             "https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py",
             FutureWarning,

src/transformers/data/metrics/__init__.py

@@ -21,7 +21,7 @@
 
 
 DEPRECATION_WARNING = (
-    "This metric will be removed from the library soon, metrics should be handled with the 🤗 Evaluate "
+    "This metric will be removed from the library soon, metrics should be handled with the Hugging Face Evaluate "
     "library. You can have a look at this example script for pointers: "
     "https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py"
 )

src/transformers/data/processors/glue.py

@@ -28,7 +28,7 @@
 logger = logging.get_logger(__name__)
 
 DEPRECATION_WARNING = (
-    "This {0} will be removed from the library soon, preprocessing should be handled with the 🤗 Datasets "
+    "This {0} will be removed from the library soon, preprocessing should be handled with the Hugging Face Datasets "
     "library. You can have a look at this example script for pointers: "
     "https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py"
 )

src/transformers/integrations/integration_utils.py

@@ -38,7 +38,7 @@
 
 
 if os.getenv("WANDB_MODE") == "offline":
-    print("⚙️  Running in WANDB offline mode")
+    print("[INFO] Running in WANDB offline mode")
 
 from .. import PreTrainedModel, TrainingArguments
 from .. import __version__ as version

src/transformers/models/audio_spectrogram_transformer/convert_audio_spectrogram_transformer_original_to_pytorch.py

@@ -272,7 +272,9 @@ def convert_audio_spectrogram_transformer_checkpoint(model_name, pytorch_dump_fo
         "--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model directory."
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
 
     args = parser.parse_args()

src/transformers/models/bros/convert_bros_to_pytorch.py

@@ -138,7 +138,7 @@ def convert_bros_checkpoint(model_name, pytorch_dump_folder_path=None, push_to_h
     parser.add_argument(
         "--push_to_hub",
         action="store_true",
-        help="Whether or not to push the converted model and processor to the 🤗 hub.",
+        help="Whether or not to push the converted model and processor to the Hugging Face hub.",
     )
 
     args = parser.parse_args()

src/transformers/models/clipseg/convert_clipseg_original_pytorch_to_hf.py

@@ -257,7 +257,9 @@ def convert_clipseg_checkpoint(model_name, checkpoint_path, pytorch_dump_folder_
         "--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model directory."
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
 
     args = parser.parse_args()

src/transformers/models/dac/convert_dac_checkpoint.py

@@ -274,7 +274,7 @@ def convert_checkpoint(
         "--pytorch_dump_folder_path", required=True, default=None, type=str, help="Path to the output PyTorch model."
     )
     parser.add_argument(
-        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the 🤗 hub."
+        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the Hugging Face hub."
     )
     parser.add_argument("--sample_rate", default=None, type=str, help="Sample rate used by DacFeatureExtractor")
     args = parser.parse_args()

src/transformers/models/data2vec/convert_data2vec_audio_original_pytorch_checkpoint_to_pytorch.py

@@ -258,7 +258,7 @@ def load_data2vec(path):
     max_absolute_diff = torch.max(torch.abs(our_output - their_output)).item()
     print(f"max_absolute_diff = {max_absolute_diff}")  # ~ 1e-7
     success = torch.allclose(our_output, their_output, atol=1e-3)
-    print("Do both models output the same tensors?", "🔥" if success else "💩")
+    print("Do both models output the same tensors?", "[PASS]" if success else "[FAIL]")
     if not success:
         raise Exception("Something went wRoNg")
 

src/transformers/models/data2vec/convert_data2vec_text_original_pytorch_checkpoint_to_pytorch.py

@@ -180,7 +180,7 @@ def convert_data2vec_checkpoint_to_pytorch(
     max_absolute_diff = torch.max(torch.abs(our_output - their_output)).item()
     print(f"max_absolute_diff = {max_absolute_diff}")  # ~ 1e-7
     success = torch.allclose(our_output, their_output, atol=1e-3)
-    print("Do both models output the same tensors?", "🔥" if success else "💩")
+    print("Do both models output the same tensors?", "[PASS]" if success else "[FAIL]")
     if not success:
         raise Exception("Something went wRoNg")
 

src/transformers/models/data2vec/convert_data2vec_vision_original_pytorch_checkpoint_to_pytorch.py

@@ -341,7 +341,7 @@ def main():
 
     print(f"max_absolute_diff = {max_absolute_diff}")
     success = torch.allclose(hf_output, orig_model_output, atol=1e-3)
-    print("Do both models output the same tensors?", "🔥" if success else "💩")
+    print("Do both models output the same tensors?", "[PASS]" if success else "[FAIL]")
     if not success:
         raise Exception("Something went wRoNg")
 

src/transformers/models/deformable_detr/convert_deformable_detr_to_pytorch.py

@@ -222,7 +222,9 @@ def convert_deformable_detr_checkpoint(
         help="Path to the folder to output PyTorch model.",
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     args = parser.parse_args()
     convert_deformable_detr_checkpoint(

src/transformers/models/deprecated/bort/convert_bort_original_gluonnlp_checkpoint_to_pytorch.py

@@ -299,9 +299,9 @@ def check_and_map_params(hf_param, gluon_param):
     success = np.allclose(gluon_layer, hf_layer, atol=1e-3)
 
     if success:
-        print("✔️ Both model do output the same tensors")
+        print("[SUCCESS] Both models do output the same tensors")
     else:
-        print("❌ Both model do **NOT** output the same tensors")
+        print("[FAIL] Both models do **NOT** output the same tensors")
         print("Absolute difference is:", max_absolute_diff)
 
 

src/transformers/models/deprecated/deta/convert_deta_resnet_to_pytorch.py

@@ -313,7 +313,9 @@ def convert_deta_checkpoint(model_name, pytorch_dump_folder_path, push_to_hub):
         help="Path to the folder to output PyTorch model.",
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     args = parser.parse_args()
     convert_deta_checkpoint(args.model_name, args.pytorch_dump_folder_path, args.push_to_hub)

src/transformers/models/deprecated/deta/convert_deta_swin_to_pytorch.py

@@ -320,7 +320,9 @@ def convert_deta_checkpoint(model_name, pytorch_dump_folder_path, push_to_hub):
         help="Path to the folder to output PyTorch model.",
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     args = parser.parse_args()
     convert_deta_checkpoint(args.model_name, args.pytorch_dump_folder_path, args.push_to_hub)

src/transformers/models/dinov2/convert_dinov2_to_hf.py

@@ -278,7 +278,9 @@ def convert_dinov2_checkpoint(model_name, pytorch_dump_folder_path, push_to_hub=
         "--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model directory."
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
 
     args = parser.parse_args()

src/transformers/models/dinov2_with_registers/convert_dinov2_with_registers_to_hf.py

@@ -284,7 +284,9 @@ def convert_dinov2_with_registers_checkpoint(model_name, pytorch_dump_folder_pat
         "--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model directory."
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
 
     args = parser.parse_args()

src/transformers/models/donut/convert_donut_to_pytorch.py

@@ -227,7 +227,7 @@ def convert_donut_checkpoint(model_name, pytorch_dump_folder_path=None, push_to_
     parser.add_argument(
         "--push_to_hub",
         action="store_true",
-        help="Whether or not to push the converted model and processor to the 🤗 hub.",
+        help="Whether or not to push the converted model and processor to the Hugging Face hub.",
     )
 
     args = parser.parse_args()

src/transformers/models/encodec/convert_encodec_checkpoint_to_pytorch.py

@@ -352,7 +352,7 @@ def convert_checkpoint(
         "--pytorch_dump_folder_path", required=True, default=None, type=str, help="Path to the output PyTorch model."
     )
     parser.add_argument(
-        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the 🤗 hub."
+        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the Hugging Face hub."
     )
 
     args = parser.parse_args()

src/transformers/models/esm/convert_esm.py

@@ -316,7 +316,7 @@ def convert_esm_checkpoint_to_pytorch(
         hf_tokens = hf_tokenizer([row[1] for row in sample_data], return_tensors="pt", padding=True)
         success = torch.all(hf_tokens["input_ids"] == batch_tokens)
 
-    print("Do both models tokenizers output the same tokens?", "🔥" if success else "💩")
+    print("Do both models tokenizers output the same tokens?", "[PASS]" if success else "[FAIL]")
     if not success:
         raise Exception("Tokenization does not match!")
 
@@ -348,7 +348,7 @@ def convert_esm_checkpoint_to_pytorch(
             success = torch.allclose(our_output, their_output, atol=1e-5)
 
         print(f"max_absolute_diff = {max_absolute_diff}")  # ~ 1e-5
-        print("Do both models output the same tensors?", "🔥" if success else "💩")
+        print("Do both models output the same tensors?", "[PASS]" if success else "[FAIL]")
 
         if not success:
             raise Exception("Something went wRoNg")
@@ -362,7 +362,7 @@ def convert_esm_checkpoint_to_pytorch(
 
             print("Contact prediction testing:")
             print(f"max_absolute_diff = {max_absolute_diff}")  # ~ 1e-5
-            print("Do both models output the same tensors?", "🔥" if success else "💩")
+            print("Do both models output the same tensors?", "[PASS]" if success else "[FAIL]")
 
             if not success:
                 raise Exception("Something went wRoNg")

src/transformers/models/fastspeech2_conformer/convert_fastspeech2_conformer_original_pytorch_checkpoint_to_pytorch.py

@@ -198,7 +198,7 @@ def convert_FastSpeech2ConformerModel_checkpoint(
         "--pytorch_dump_folder_path", required=True, default=None, type=str, help="Path to the output PyTorch model."
     )
     parser.add_argument(
-        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the 🤗 hub."
+        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the Hugging Face hub."
     )
 
     args = parser.parse_args()

src/transformers/models/fastspeech2_conformer/convert_hifigan.py

@@ -122,7 +122,7 @@ def convert_hifigan_checkpoint(
         "--pytorch_dump_folder_path", required=True, default=None, type=str, help="Path to the output PyTorch model."
     )
     parser.add_argument(
-        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the 🤗 hub."
+        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the Hugging Face hub."
     )
 
     args = parser.parse_args()

src/transformers/models/fastspeech2_conformer/convert_model_with_hifigan.py

@@ -89,7 +89,7 @@ def convert_FastSpeech2ConformerWithHifiGan_checkpoint(
         help="Path to the output `FastSpeech2ConformerModel` PyTorch model.",
     )
     parser.add_argument(
-        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the 🤗 hub."
+        "--push_to_hub", default=None, type=str, help="Where to upload the converted model on the Hugging Face hub."
     )
 
     args = parser.parse_args()

src/transformers/models/got_ocr2/convert_got_ocr2_weights_to_hf.py

@@ -250,7 +250,9 @@ def main():
     )
 
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     args = parser.parse_args()
     write_tokenizer(

src/transformers/models/grounding_dino/convert_grounding_dino_to_hf.py

@@ -481,7 +481,9 @@ def convert_grounding_dino_checkpoint(args):
         "--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model directory."
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     parser.add_argument(
         "--verify_logits", action="store_false", help="Whether or not to verify logits after conversion."

src/transformers/models/groupvit/convert_groupvit_nvlab_to_hf.py

@@ -210,7 +210,7 @@ def convert_groupvit_checkpoint(
     parser.add_argument(
         "--push_to_hub",
         action="store_true",
-        help="Whether or not to push the converted model and processor to the 🤗 hub using the provided `model_name`.",
+        help="Whether or not to push the converted model and processor to the Hugging Face hub using the provided `model_name`.",
     )
     args = parser.parse_args()
 

src/transformers/models/hiera/convert_hiera_to_hf.py

@@ -353,7 +353,9 @@ def convert_hiera_checkpoint(args):
         help="Whether or not to verify the logits against the original implementation.",
     )
     parser.add_argument(
-        "--push-to-hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push-to-hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     parser.add_argument(
         "--base-model",

src/transformers/models/ijepa/convert_ijepa_to_hf.py

@@ -253,7 +253,7 @@ def main():
     parser.add_argument(
         "--push_to_hub",
         action="store_true",
-        help="Whether or not to push the model to the 🤗 Hub.",
+        help="Whether or not to push the model to the Hugging Face Hub.",
     )
     parser.add_argument(
         "--verify_logits", action="store_false", help="Whether or not to verify logits after conversion."

src/transformers/models/internvl/convert_internvl_weights_to_hf.py

@@ -433,7 +433,9 @@ def main():
     )
 
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     args = parser.parse_args()
     write_tokenizer(

src/transformers/models/llava_next/convert_llava_next_weights_to_hf.py

@@ -387,7 +387,9 @@ def convert_llava_to_hf(model_id, pytorch_dump_folder_path, push_to_hub=False):
         "--pytorch_dump_folder_path", type=str, required=True, help="Path to the output PyTorch model directory."
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     args = parser.parse_args()
 

src/transformers/models/llava_next_video/convert_llava_next_video_weights_to_hf.py

@@ -267,7 +267,9 @@ def convert_llava_to_hf(model_id, pytorch_dump_folder_path, push_to_hub=False):
         "--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model directory."
     )
     parser.add_argument(
-        "--push_to_hub", action="store_true", help="Whether or not to push the converted model to the 🤗 hub."
+        "--push_to_hub",
+        action="store_true",
+        help="Whether or not to push the converted model to the Hugging Face hub.",
     )
     args = parser.parse_args()