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")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("seiching/whisper-large-seiching") model = AutoModelForSpeechSeq2Seq.from_pretrained("seiching/whisper-large-seiching") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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:a4a66dcca5570e089ca3d786b512da09785b30193e6e9089c7f163ad4b6e747d
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size 6173370152
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