Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Italian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use whispy/whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whispy/whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="whispy/whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("whispy/whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("whispy/whisper") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:0d42902a49ea2d7533e94700296227c4eae41924cb979c2fa8f7f5af702a25c1
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size 966995080
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