Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Chinese
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use seiching/whisper-medium-seiching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seiching/whisper-medium-seiching with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="seiching/whisper-medium-seiching")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("seiching/whisper-medium-seiching") model = AutoModelForSpeechSeq2Seq.from_pretrained("seiching/whisper-medium-seiching", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
update model card README.md
4552303 -
End of training
ba9cdce -
Training in progress, step 4000
489d6e4 -
Training in progress, step 3500
0247a40 -
Training in progress, step 3000
7c23925 -
Training in progress, step 2500
b1e3931 -
Training in progress, step 2000
7bafe5d -
Training in progress, step 1500
22a1465 -
Training in progress, step 1000
ceebef9 -
Training in progress, step 500
9aed245
-
Training in progress, step 3500
365d939 -
Training in progress, step 3000
a312f9a -
Training in progress, step 2500
e4de737 -
Training in progress, step 2000
a2d952d -
Training in progress, step 1500
472c0bc -
Training in progress, step 1000
9850515 -
Training in progress, step 500
2f55dc4
-
Training in progress, step 4000
df957f3 -
Training in progress, step 3500
6cc369a -
Training in progress, step 3000
7b1c036 -
Training in progress, step 2500
7c37b84 -
Training in progress, step 2000
8850d64 -
Training in progress, step 1500
1c0aebe -
Training in progress, step 1000
a6811cf -
Training in progress, step 500
11224e3
-
initial commit
Verified signaturee7f48f3