Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hindi
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
robust-speech-event
model_for_talk
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8 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-hi-cv8 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-hi-cv8")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8") model = AutoModelForCTC.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2457d2bacae8165f8be81b12db816d34b36f59275415481c9266b8e28d62c3b5
- Size of remote file:
- 1.26 GB
- SHA256:
- 5547c63fdd1b56926ff8f75c0e41b0e75f09dcec445146ebace689d7b55fae38
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