Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Dev372/HarshDev-whisper-small-English_4000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dev372/HarshDev-whisper-small-English_4000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Dev372/HarshDev-whisper-small-English_4000")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Dev372/HarshDev-whisper-small-English_4000") model = AutoModelForSpeechSeq2Seq.from_pretrained("Dev372/HarshDev-whisper-small-English_4000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cccd079264e0d8765e23277fca1109c5c3f318ecd32e068700feb228ac3dbd08
- Size of remote file:
- 5.3 kB
- SHA256:
- 52c71938cabc24e78996dbb59277c2ac846354f1e11f669a5a438bad8ba1bc41
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