Automatic Speech Recognition
Transformers
PyTorch
Finnish
wav2vec2
Generated from Trainer
mozilla-foundation/common_voice_7_0
audio
speech
Instructions to use RASMUS/wav2vec2-xlsr-fi-train-aug-bigLM-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RASMUS/wav2vec2-xlsr-fi-train-aug-bigLM-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RASMUS/wav2vec2-xlsr-fi-train-aug-bigLM-1B")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("RASMUS/wav2vec2-xlsr-fi-train-aug-bigLM-1B") model = AutoModelForCTC.from_pretrained("RASMUS/wav2vec2-xlsr-fi-train-aug-bigLM-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a4d34d16076bf271283d1f608870450e799ae96b9a8b1b7c8809ab0394cb7e9
- Size of remote file:
- 3.85 GB
- SHA256:
- b096a40cf8461209f7d10903647e7c13c8572bd630b9f8ac41a1d184b1e986bb
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