Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use dennohpeter/low-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dennohpeter/low-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="dennohpeter/low-german")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("dennohpeter/low-german") model = AutoModelForCTC.from_pretrained("dennohpeter/low-german") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a5875440d0c89ad439d5f97a5e0fe8fd03838bf28e219987d100cc171e46cf3
- Size of remote file:
- 5.78 kB
- SHA256:
- c457709ae0541b6604ddf2a54c5e58cbc27b31d06515720903a8af2efc42b472
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