Automatic Speech Recognition
Transformers
PyTorch
English
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use fxmarty/whisper-tiny-working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fxmarty/whisper-tiny-working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="fxmarty/whisper-tiny-working")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("fxmarty/whisper-tiny-working") model = AutoModelForSpeechSeq2Seq.from_pretrained("fxmarty/whisper-tiny-working") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:f558c6f15dffff639f1b972b070c0df0227d05b5ba9b8d316636941aa57df1d9
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size 11250784
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