Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use 3funnn/wav2vec2-base-librispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 3funnn/wav2vec2-base-librispeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="3funnn/wav2vec2-base-librispeech")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("3funnn/wav2vec2-base-librispeech") model = AutoModelForCTC.from_pretrained("3funnn/wav2vec2-base-librispeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6a8f73b9d171852060d615e6c08097585e7039009ad69ee436fcf8c7fcc715a
- Size of remote file:
- 4.73 kB
- SHA256:
- f5da6855d990d2d990e877d90e57036a3f8a2e81150b11889f65d81c776c8935
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