Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Tatar
whisper
whisper-event
Eval Results (legacy)
Instructions to use 501Good/whisper-tiny-tt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 501Good/whisper-tiny-tt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="501Good/whisper-tiny-tt")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("501Good/whisper-tiny-tt") model = AutoModelForSpeechSeq2Seq.from_pretrained("501Good/whisper-tiny-tt") - 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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version https://git-lfs.github.com/spec/v1
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oid sha256:c206eb4403d9bbad96f688e97fa1c4d562dfa1fa38133a641dd57ed09f9495e1
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size 151061672
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