Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Chinese
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use seiching/whisper-large-seiching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seiching/whisper-large-seiching with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="seiching/whisper-large-seiching")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("seiching/whisper-large-seiching") model = AutoModelForSpeechSeq2Seq.from_pretrained("seiching/whisper-large-seiching", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 3000
Browse files
pytorch_model.bin
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runs/Jan29_16-17-18_jupyter-207331-40cpc-2ecom-2etw/events.out.tfevents.1706516251.jupyter-207331-40cpc-2ecom-2etw.537.1
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