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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Kleber/output_dir") model = AutoModelForSpeechSeq2Seq.from_pretrained("Kleber/output_dir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.2a047a5
-
Training in progress, step 2000
b605ce5 -
Training in progress, step 1000
b4f705c -
update model card README.md
d2828b3 -
End of training
b2f1396 -
update model card README.md
05576ea -
Model save
f1833e8 -
Training in progress, step 5000
2e97489
-
Training in progress, step 4000
ca38867 -
Training in progress, step 3000
3abeb48 -
Training in progress, step 2000
335f2e7 -
Training in progress, step 1000
0a2bf9e -
initial commit
e76143c