Gobee
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Wav2vec2-Large-XLSR-Tamil

Automatic Speech Recognition

xlsr-fine-tuning-week

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Inference Endpoints

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Gobee commited on Nov 19, 2022

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eb8cb9e

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1 Parent(s): f30644f

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@@ -43,8 +43,8 @@ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 test_dataset = load_dataset("common_voice", "ta", split="test[:2%]").
-processor = Wav2Vec2Processor.from_pretrained("manandey/wav2vec2-large-xlsr-tamil")
-model = Wav2Vec2ForCTC.from_pretrained("manandey/wav2vec2-large-xlsr-tamil")
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
@@ -83,8 +83,8 @@ import re
 test_dataset = load_dataset("common_voice", "ta", split="test")
 wer = load_metric("wer")
-processor = Wav2Vec2Processor.from_pretrained("manandey/wav2vec2-large-xlsr-tamil")
-model = Wav2Vec2ForCTC.from_pretrained("manandey/wav2vec2-large-xlsr-tamil")
 model.to("cuda")
 chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\ \’\–\(\)]'

 test_dataset = load_dataset("common_voice", "ta", split="test[:2%]").
+processor = Wav2Vec2Processor.from_pretrained("Gobee/Wav2vec2-Large-XLSR-Tamil")
+model = Wav2Vec2ForCTC.from_pretrained("Gobee/Wav2vec2-Large-XLSR-Tamil")
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 test_dataset = load_dataset("common_voice", "ta", split="test")
 wer = load_metric("wer")
+processor = Wav2Vec2Processor.from_pretrained("Gobee/Wav2vec2-Large-XLSR-Tamil")
+model = Wav2Vec2ForCTC.from_pretrained("Gobee/Wav2vec2-Large-XLSR-Tamil")
 model.to("cuda")
 chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\ \’\–\(\)]'