Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Kinyarwanda
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Kleber/output_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kleber/output_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Kleber/output_dir")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Kleber/output_dir") model = AutoModelForSpeechSeq2Seq.from_pretrained("Kleber/output_dir") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2ab227a804f1f931ce705b32616eb85108f5659fa002ecdcbf3fdc36b15c4fb4
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size 966995080
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