Instructions to use SamagraDataGov/whisper-test-quant_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamagraDataGov/whisper-test-quant_quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SamagraDataGov/whisper-test-quant_quantized")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SamagraDataGov/whisper-test-quant_quantized") model = AutoModelForSpeechSeq2Seq.from_pretrained("SamagraDataGov/whisper-test-quant_quantized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1da946b549260da0fe25b79c8f02bb7fc34d8b42adf4e43ff4e824a8158e04a5
- Size of remote file:
- 75.5 MB
- SHA256:
- 9e090a886fd8be434d4b7ca9c7e136da15a7b3a9d6bcaaab549b2e31c28329d6
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