Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Yue Chinese
whisper
whisper-event
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use simonl0909/whisper-large-v2-cantonese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonl0909/whisper-large-v2-cantonese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="simonl0909/whisper-large-v2-cantonese")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("simonl0909/whisper-large-v2-cantonese") model = AutoModelForSpeechSeq2Seq.from_pretrained("simonl0909/whisper-large-v2-cantonese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b43ba0bf87556d6e09aeb9011ffad2827455b686f0b34c3ac442af784ae31566
- Size of remote file:
- 6.17 GB
- SHA256:
- 627e53e43406dd47dedb09249f69657cbaaf4c3c1184940ff593832ee948f4b2
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