Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Serbian
wav2vec2
Generated from Trainer
hf-asr-leaderboard
model_for_talk
mozilla-foundation/common_voice_8_0
robust-speech-event
Eval Results (legacy)
Instructions to use DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4") model = AutoModelForCTC.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 451f0af
Update README.md
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README.md
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datasets:
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- common_voice
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model-index:
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- name: wav2vec2-large-xls-r-300m-
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results:
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- task:
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name: Automatic Speech Recognition
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datasets:
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- common_voice
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model-index:
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- name: wav2vec2-large-xls-r-300m-sr-v4
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results:
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- task:
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name: Automatic Speech Recognition
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