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huggingface · Oct 10, 2022 · 5fa46be · 5fa46be
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Showing 2 changed files with 14 additions and 14 deletions.
diff --git a/src/transformers/models/whisper/modeling_tf_whisper.py b/src/transformers/models/whisper/modeling_tf_whisper.py
@@ -1030,7 +1030,7 @@ def call(
          >>> from transformers import TFWhisperModel, WhisperFeatureExtractor
          >>> from datasets import load_dataset
 
-         >>> model = TFWhisperModel.from_pretrained("openai/whisper-base", from_pt=True)
+         >>> model = TFWhisperModel.from_pretrained("openai/whisper-base")
          >>> feature_extractor = WhisperFeatureExtractor.from_pretrained("openai/whisper-base")
          >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
          >>> inputs = feature_extractor(
@@ -1157,7 +1157,7 @@ def call(
          >>> from transformers import TFWhisperModel, WhisperFeatureExtractor
          >>> from datasets import load_dataset
 
-         >>> model = TFWhisperModel.from_pretrained("openai/whisper-base", from_pt=True)
+         >>> model = TFWhisperModel.from_pretrained("openai/whisper-base")
          >>> feature_extractor = WhisperFeatureExtractor.from_pretrained("openai/whisper-base")
          >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
          >>> inputs = feature_extractor(
@@ -1281,7 +1281,7 @@ def call(
         >>> from datasets import load_dataset
 
         >>> processor = WhisperProcessor.from_pretrained("openai/whisper-tiny.en")
-        >>> model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en", from_pt=True)
+        >>> model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
 
         >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
 

diff --git a/tests/models/whisper/test_modeling_tf_whisper.py b/tests/models/whisper/test_modeling_tf_whisper.py
@@ -644,7 +644,7 @@ def _load_datasamples(self, num_samples):
     @slow
     def test_tiny_logits_librispeech(self):
         set_seed(0)
-        model = TFWhisperModel.from_pretrained("openai/whisper-tiny", from_pt=True)
+        model = TFWhisperModel.from_pretrained("openai/whisper-tiny")
         input_speech = self._load_datasamples(1)
         feature_extractor = WhisperFeatureExtractor()
         input_features = feature_extractor(input_speech, return_tensors="tf").input_features
@@ -687,7 +687,7 @@ def test_tiny_logits_librispeech(self):
     @slow
     def test_small_en_logits_librispeech(self):
         set_seed(0)
-        model = TFWhisperModel.from_pretrained("openai/whisper-small.en", from_pt=True)
+        model = TFWhisperModel.from_pretrained("openai/whisper-small.en")
 
         input_speech = self._load_datasamples(1)
 
@@ -721,7 +721,7 @@ def test_small_en_logits_librispeech(self):
     def test_large_logits_librispeech(self):
         set_seed(0)
 
-        model = TFWhisperModel.from_pretrained("openai/whisper-large", from_pt=True)
+        model = TFWhisperModel.from_pretrained("openai/whisper-large")
 
         input_speech = self._load_datasamples(1)
 
@@ -757,7 +757,7 @@ def test_large_logits_librispeech(self):
     def test_tiny_en_generation(self):
         set_seed(0)
         processor = WhisperProcessor.from_pretrained("openai/whisper-tiny.en")
-        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en", from_pt=True)
+        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
         model.config.decoder_start_token_id = 50257
 
         input_speech = self._load_datasamples(1)
@@ -776,7 +776,7 @@ def test_tiny_en_generation(self):
     def test_tiny_generation(self):
         set_seed(0)
         processor = WhisperProcessor.from_pretrained("openai/whisper-tiny")
-        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny", from_pt=True)
+        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny")
 
         input_speech = self._load_datasamples(1)
         input_features = processor.feature_extractor(raw_speech=input_speech, return_tensors="tf").input_features
@@ -794,7 +794,7 @@ def test_tiny_generation(self):
     def test_tiny_xla_generation(self):
         set_seed(0)
         processor = WhisperProcessor.from_pretrained("openai/whisper-tiny")
-        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny", from_pt=True)
+        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny")
 
         input_speech = self._load_datasamples(1)
         input_features = processor.feature_extractor(raw_speech=input_speech, return_tensors="tf").input_features
@@ -818,7 +818,7 @@ def test_tiny_xla_generation(self):
     def test_large_generation(self):
         set_seed(0)
         processor = WhisperProcessor.from_pretrained("openai/whisper-large")
-        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-large", from_pt=True)
+        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-large")
 
         input_speech = self._load_datasamples(1)
         input_features = processor.feature_extractor(raw_speech=input_speech, return_tensors="tf").input_features
@@ -837,7 +837,7 @@ def test_large_generation(self):
     def test_large_generation_multilingual(self):
         set_seed(0)
         processor = WhisperProcessor.from_pretrained("openai/whisper-large")
-        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-large", from_pt=True)
+        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-large")
 
         ds = load_dataset("common_voice", "ja", split="test", streaming=True)
         ds = ds.cast_column("audio", datasets.Audio(sampling_rate=16_000))
@@ -872,7 +872,7 @@ def test_large_generation_multilingual(self):
     def test_large_batched_generation(self):
         set_seed(0)
         processor = WhisperProcessor.from_pretrained("openai/whisper-large")
-        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-large", from_pt=True)
+        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-large")
 
         input_speech = self._load_datasamples(4)
         input_features = processor.feature_extractor(raw_speech=input_speech, return_tensors="tf").input_features
@@ -907,7 +907,7 @@ def test_large_batched_generation(self):
     def test_tiny_en_batched_generation(self):
         set_seed(0)
         processor = WhisperProcessor.from_pretrained("openai/whisper-tiny.en")
-        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en", from_pt=True)
+        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
 
         input_speech = self._load_datasamples(4)
         input_features = processor.feature_extractor(raw_speech=input_speech, return_tensors="tf").input_features
@@ -943,7 +943,7 @@ def test_tiny_en_batched_generation(self):
     def test_tiny_en_batched_xla_generation(self):
         set_seed(0)
         processor = WhisperProcessor.from_pretrained("openai/whisper-tiny.en")
-        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en", from_pt=True)
+        model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
 
         input_speech = self._load_datasamples(4)
         input_features = processor.feature_extractor(raw_speech=input_speech, return_tensors="tf").input_features