diff --git a/docs/source/model_doc/speech_to_text.rst b/docs/source/model_doc/speech_to_text.rst index 3b84fede85..aa67672947 100644 --- a/docs/source/model_doc/speech_to_text.rst +++ b/docs/source/model_doc/speech_to_text.rst @@ -66,7 +66,7 @@ be installed as follows: ``apt install libsndfile1-dev`` ... batch["speech"] = speech ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> inputs = processor(ds["speech"][0], sampling_rate=16_000, return_tensors="pt") @@ -98,7 +98,7 @@ be installed as follows: ``apt install libsndfile1-dev`` ... batch["speech"] = speech ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> inputs = processor(ds["speech"][0], sampling_rate=16_000, return_tensors="pt") diff --git a/docs/source/model_doc/speech_to_text_2.rst b/docs/source/model_doc/speech_to_text_2.rst index 0f179b5caa..0a39999217 100644 --- a/docs/source/model_doc/speech_to_text_2.rst +++ b/docs/source/model_doc/speech_to_text_2.rst @@ -68,7 +68,7 @@ predicted token ids. ... batch["speech"] = speech ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> inputs = processor(ds["speech"][0], sampling_rate=16_000, return_tensors="pt") @@ -86,7 +86,7 @@ predicted token ids. >>> from datasets import load_dataset >>> from transformers import pipeline - >>> librispeech_en = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> librispeech_en = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> asr = pipeline("automatic-speech-recognition", model="facebook/s2t-wav2vec2-large-en-de", feature_extractor="facebook/s2t-wav2vec2-large-en-de") >>> translation_de = asr(librispeech_en[0]["file"]) diff --git a/examples/pytorch/test_examples.py b/examples/pytorch/test_examples.py index 0a98399155..9692a6eb46 100644 --- a/examples/pytorch/test_examples.py +++ b/examples/pytorch/test_examples.py @@ -391,7 +391,7 @@ class ExamplesTests(TestCasePlus): run_speech_recognition_ctc.py --output_dir {tmp_dir} --model_name_or_path hf-internal-testing/tiny-random-wav2vec2 - --dataset_name patrickvonplaten/librispeech_asr_dummy + --dataset_name hf-internal-testing/librispeech_asr_dummy --dataset_config_name clean --train_split_name validation --eval_split_name validation @@ -460,7 +460,7 @@ class ExamplesTests(TestCasePlus): run_wav2vec2_pretraining_no_trainer.py --output_dir {tmp_dir} --model_name_or_path hf-internal-testing/tiny-random-wav2vec2 - --dataset_name patrickvonplaten/librispeech_asr_dummy + --dataset_name hf-internal-testing/librispeech_asr_dummy --dataset_config_names clean --dataset_split_names validation --learning_rate 1e-4 diff --git a/examples/research_projects/wav2vec2/README.md b/examples/research_projects/wav2vec2/README.md index ba3b344089..235284840c 100644 --- a/examples/research_projects/wav2vec2/README.md +++ b/examples/research_projects/wav2vec2/README.md @@ -155,7 +155,7 @@ run_asr.py \ --per_device_eval_batch_size=2 --evaluation_strategy=steps --save_steps=500 --eval_steps=100 \ --logging_steps=5 --learning_rate=5e-4 --warmup_steps=3000 \ --model_name_or_path=patrickvonplaten/wav2vec2_tiny_random_robust \ ---dataset_name=patrickvonplaten/librispeech_asr_dummy --dataset_config_name=clean \ +--dataset_name=hf-internal-testing/librispeech_asr_dummy --dataset_config_name=clean \ --train_split_name=validation --validation_split_name=validation --orthography=timit \ --preprocessing_num_workers=1 --group_by_length --freeze_feature_extractor --verbose_logging \ --deepspeed ds_config_wav2vec2_zero2.json @@ -179,7 +179,7 @@ run_asr.py \ --per_device_eval_batch_size=2 --evaluation_strategy=steps --save_steps=500 --eval_steps=100 \ --logging_steps=5 --learning_rate=5e-4 --warmup_steps=3000 \ --model_name_or_path=patrickvonplaten/wav2vec2_tiny_random_robust \ ---dataset_name=patrickvonplaten/librispeech_asr_dummy --dataset_config_name=clean \ +--dataset_name=hf-internal-testing/librispeech_asr_dummy --dataset_config_name=clean \ --train_split_name=validation --validation_split_name=validation --orthography=timit \ --preprocessing_num_workers=1 --group_by_length --freeze_feature_extractor --verbose_logging \ --deepspeed ds_config_wav2vec2_zero3.json diff --git a/examples/research_projects/wav2vec2/test_wav2vec2_deepspeed.py b/examples/research_projects/wav2vec2/test_wav2vec2_deepspeed.py index 3a00fbd941..a414f7db97 100644 --- a/examples/research_projects/wav2vec2/test_wav2vec2_deepspeed.py +++ b/examples/research_projects/wav2vec2/test_wav2vec2_deepspeed.py @@ -155,7 +155,7 @@ class TestDeepSpeedWav2Vec2(TestCasePlus): output_dir = self.get_auto_remove_tmp_dir("./xxx", after=False) args = f""" --model_name_or_path {model_name} - --dataset_name patrickvonplaten/librispeech_asr_dummy + --dataset_name hf-internal-testing/librispeech_asr_dummy --dataset_config_name clean --train_split_name validation --validation_split_name validation diff --git a/src/transformers/models/hubert/modeling_hubert.py b/src/transformers/models/hubert/modeling_hubert.py index 2aa1626871..6123d7e6f8 100755 --- a/src/transformers/models/hubert/modeling_hubert.py +++ b/src/transformers/models/hubert/modeling_hubert.py @@ -953,7 +953,7 @@ class HubertModel(HubertPreTrainedModel): ... batch["speech"] = speech ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="pt").input_values # Batch size 1 @@ -1059,7 +1059,7 @@ class HubertForCTC(HubertPreTrainedModel): ... batch["speech"] = speech ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="pt").input_values # Batch size 1 diff --git a/src/transformers/models/hubert/modeling_tf_hubert.py b/src/transformers/models/hubert/modeling_tf_hubert.py index 0d5df863e0..44867fe586 100644 --- a/src/transformers/models/hubert/modeling_tf_hubert.py +++ b/src/transformers/models/hubert/modeling_tf_hubert.py @@ -1412,7 +1412,7 @@ class TFHubertModel(TFHubertPreTrainedModel): ... batch["speech"] = speech ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="tf").input_values # Batch size 1 @@ -1522,7 +1522,7 @@ class TFHubertForCTC(TFHubertPreTrainedModel): ... batch["speech"] = speech ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="tf").input_values # Batch size 1 diff --git a/src/transformers/models/speech_encoder_decoder/modeling_speech_encoder_decoder.py b/src/transformers/models/speech_encoder_decoder/modeling_speech_encoder_decoder.py index a576caff58..4207067a46 100644 --- a/src/transformers/models/speech_encoder_decoder/modeling_speech_encoder_decoder.py +++ b/src/transformers/models/speech_encoder_decoder/modeling_speech_encoder_decoder.py @@ -414,7 +414,7 @@ class SpeechEncoderDecoderModel(PreTrainedModel): >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="pt").input_values # Batch size 1 diff --git a/src/transformers/models/speech_to_text/modeling_speech_to_text.py b/src/transformers/models/speech_to_text/modeling_speech_to_text.py index e91af884c6..9a8f364338 100755 --- a/src/transformers/models/speech_to_text/modeling_speech_to_text.py +++ b/src/transformers/models/speech_to_text/modeling_speech_to_text.py @@ -1306,7 +1306,7 @@ class Speech2TextForConditionalGeneration(Speech2TextPreTrainedModel): >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_features = processor(ds["speech"][0], sampling_rate=16000, return_tensors="pt").input_features # Batch size 1 diff --git a/src/transformers/models/wav2vec2/modeling_flax_wav2vec2.py b/src/transformers/models/wav2vec2/modeling_flax_wav2vec2.py index 3d35e0f359..82273cd1d2 100644 --- a/src/transformers/models/wav2vec2/modeling_flax_wav2vec2.py +++ b/src/transformers/models/wav2vec2/modeling_flax_wav2vec2.py @@ -944,7 +944,7 @@ FLAX_WAV2VEC2_MODEL_DOCSTRING = """ >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], sampling_rate=16_000, return_tensors="np").input_values # Batch size 1 @@ -1045,7 +1045,7 @@ FLAX_WAV2VEC2_FOR_CTC_DOCSTRING = """ >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], sampling_rate=16_000, return_tensors="np").input_values # Batch size 1 @@ -1233,7 +1233,7 @@ FLAX_WAV2VEC2_FOR_PRETRAINING_DOCSTRING = """ ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = feature_extractor(ds["speech"][0], return_tensors="np").input_values # Batch size 1 diff --git a/src/transformers/models/wav2vec2/modeling_tf_wav2vec2.py b/src/transformers/models/wav2vec2/modeling_tf_wav2vec2.py index 3b04ccbb79..3d724bda96 100644 --- a/src/transformers/models/wav2vec2/modeling_tf_wav2vec2.py +++ b/src/transformers/models/wav2vec2/modeling_tf_wav2vec2.py @@ -1406,7 +1406,7 @@ class TFWav2Vec2Model(TFWav2Vec2PreTrainedModel): >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="tf").input_values # Batch size 1 @@ -1516,7 +1516,7 @@ class TFWav2Vec2ForCTC(TFWav2Vec2PreTrainedModel): >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="tf").input_values # Batch size 1 diff --git a/src/transformers/models/wav2vec2/modeling_wav2vec2.py b/src/transformers/models/wav2vec2/modeling_wav2vec2.py index e62186eb99..6a24d554a8 100755 --- a/src/transformers/models/wav2vec2/modeling_wav2vec2.py +++ b/src/transformers/models/wav2vec2/modeling_wav2vec2.py @@ -1146,7 +1146,7 @@ class Wav2Vec2Model(Wav2Vec2PreTrainedModel): >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="pt").input_values # Batch size 1 @@ -1280,7 +1280,7 @@ class Wav2Vec2ForPreTraining(Wav2Vec2PreTrainedModel): ... return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = feature_extractor(ds["speech"][0], return_tensors="pt").input_values # Batch size 1 @@ -1442,7 +1442,7 @@ class Wav2Vec2ForMaskedLM(Wav2Vec2PreTrainedModel): >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="pt").input_values # Batch size 1 @@ -1536,7 +1536,7 @@ class Wav2Vec2ForCTC(Wav2Vec2PreTrainedModel): >>> batch["speech"] = speech >>> return batch - >>> ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") >>> ds = ds.map(map_to_array) >>> input_values = processor(ds["speech"][0], return_tensors="pt").input_values # Batch size 1 diff --git a/tests/test_modeling_flax_wav2vec2.py b/tests/test_modeling_flax_wav2vec2.py index ce83d77f9f..07a4ee73e3 100644 --- a/tests/test_modeling_flax_wav2vec2.py +++ b/tests/test_modeling_flax_wav2vec2.py @@ -366,7 +366,7 @@ class FlaxWav2Vec2ModelIntegrationTest(unittest.TestCase): batch["speech"] = speech return batch - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") ds = ds.filter(lambda x: x["id"] in ids).sort("id").map(map_to_array) diff --git a/tests/test_modeling_hubert.py b/tests/test_modeling_hubert.py index 38e47103c4..486b44f404 100644 --- a/tests/test_modeling_hubert.py +++ b/tests/test_modeling_hubert.py @@ -623,7 +623,7 @@ class HubertModelIntegrationTest(unittest.TestCase): batch["speech"] = speech return batch - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") ds = ds.filter(lambda x: x["id"] in ids).sort("id").map(map_to_array) diff --git a/tests/test_modeling_speech_to_text.py b/tests/test_modeling_speech_to_text.py index 44a98eb4cf..59211cc33b 100644 --- a/tests/test_modeling_speech_to_text.py +++ b/tests/test_modeling_speech_to_text.py @@ -723,7 +723,7 @@ class Speech2TextModelIntegrationTests(unittest.TestCase): batch["speech"] = speech return batch - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") ds = ds.sort("id").select(range(num_samples)).map(map_to_array) return ds["speech"][:num_samples] diff --git a/tests/test_modeling_tf_hubert.py b/tests/test_modeling_tf_hubert.py index 7e85519553..3091ebed67 100644 --- a/tests/test_modeling_tf_hubert.py +++ b/tests/test_modeling_tf_hubert.py @@ -489,7 +489,7 @@ class TFHubertModelIntegrationTest(unittest.TestCase): batch["speech"] = speech return batch - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") ds = ds.filter(lambda x: x["id"] in ids).sort("id").map(map_to_array) diff --git a/tests/test_modeling_tf_wav2vec2.py b/tests/test_modeling_tf_wav2vec2.py index c7844ad4b2..b46ef5ae9f 100644 --- a/tests/test_modeling_tf_wav2vec2.py +++ b/tests/test_modeling_tf_wav2vec2.py @@ -489,7 +489,7 @@ class TFWav2Vec2ModelIntegrationTest(unittest.TestCase): batch["speech"] = speech return batch - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") ds = ds.filter(lambda x: x["id"] in ids).sort("id").map(map_to_array) diff --git a/tests/test_modeling_wav2vec2.py b/tests/test_modeling_wav2vec2.py index 13ef539d46..0ea1bee3b1 100644 --- a/tests/test_modeling_wav2vec2.py +++ b/tests/test_modeling_wav2vec2.py @@ -910,7 +910,7 @@ class Wav2Vec2ModelIntegrationTest(unittest.TestCase): batch["speech"] = speech return batch - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") ds = ds.filter(lambda x: x["id"] in ids).sort("id").map(map_to_array) diff --git a/tests/test_pipelines_audio_classification.py b/tests/test_pipelines_audio_classification.py index a31292f390..561d333caa 100644 --- a/tests/test_pipelines_audio_classification.py +++ b/tests/test_pipelines_audio_classification.py @@ -62,7 +62,7 @@ class AudioClassificationPipelineTests(unittest.TestCase, metaclass=PipelineTest ) # test with a local file - dataset = datasets.load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") + dataset = datasets.load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation") filename = dataset[0]["file"] output = audio_classifier(filename) self.assertEqual( diff --git a/tests/test_pipelines_automatic_speech_recognition.py b/tests/test_pipelines_automatic_speech_recognition.py index 704cd80496..e2f7644859 100644 --- a/tests/test_pipelines_automatic_speech_recognition.py +++ b/tests/test_pipelines_automatic_speech_recognition.py @@ -74,7 +74,7 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase): from datasets import load_dataset - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation").sort("id") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation").sort("id") filename = ds[40]["file"] output = speech_recognizer(filename) self.assertEqual(output, {"text": "A MAN SAID TO THE UNIVERSE SIR I EXIST"}) @@ -92,7 +92,7 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase): from datasets import load_dataset - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation").sort("id") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation").sort("id") filename = ds[40]["file"] output = speech_recognizer(filename) self.assertEqual(output, {"text": 'Ein Mann sagte zum Universum : " Sir, ich existiert! "'}) @@ -114,7 +114,7 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase): output = asr(waveform) self.assertEqual(output, {"text": ""}) - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation").sort("id") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation").sort("id") filename = ds[40]["file"] output = asr(filename) self.assertEqual(output, {"text": "A MAN SAID TO THE UNIVERSE SIR I EXIST"}) @@ -144,7 +144,7 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase): output = asr(waveform) self.assertEqual(output, {"text": "(Applausi)"}) - ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation").sort("id") + ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation").sort("id") filename = ds[40]["file"] output = asr(filename) self.assertEqual(output, {"text": "Un uomo disse all'universo: \"Signore, io esisto."})