Automatic Speech Recognition
Transformers
PyTorch
Slovenian
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-sl-with-LM-v2 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-sl-with-LM-v2 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-sl-with-LM-v2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v2") model = AutoModelForCTC.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3a18a0bf025416dd5a8e5402e6c4ff4e6bff816d789b5f317ca2cfbb019470f
- Size of remote file:
- 1.26 GB
- SHA256:
- f25488bc982e9d77e1f779120badbecede1f5f3d590fa635eb5850ac2a3c498f
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