Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Czech
wav2vec2
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_8_0
robust-speech-event
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use comodoro/wav2vec2-xls-r-300m-cs-250 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use comodoro/wav2vec2-xls-r-300m-cs-250 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="comodoro/wav2vec2-xls-r-300m-cs-250")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("comodoro/wav2vec2-xls-r-300m-cs-250") model = AutoModelForCTC.from_pretrained("comodoro/wav2vec2-xls-r-300m-cs-250") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dba8cb498c918277cd8da66d8374dbc6e457efa8ac7011fb50d401d96f528eec
- Size of remote file:
- 1.26 GB
- SHA256:
- ef2fdad28a59d6ae8772619eba69fa0ee09714a6b9c27d55717b32629b201ead
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