Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Persian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use benchmarkcentral/whisper-small-fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benchmarkcentral/whisper-small-fa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="benchmarkcentral/whisper-small-fa")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("benchmarkcentral/whisper-small-fa") model = AutoModelForSpeechSeq2Seq.from_pretrained("benchmarkcentral/whisper-small-fa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 484ff679ea50fcda9e6365e7cd98c3c2ded24affd7325ffee2b95e95ff4fcb35
- Size of remote file:
- 5.3 kB
- SHA256:
- 421d94730d23ffdb5ccf5a95966caa7314c8bfdfa0e73a7197a4ca34e3400202
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