Automatic Speech Recognition
Transformers
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use razhan/whisper-base-hawrami-transcription with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razhan/whisper-base-hawrami-transcription with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="razhan/whisper-base-hawrami-transcription")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("razhan/whisper-base-hawrami-transcription") model = AutoModelForSpeechSeq2Seq.from_pretrained("razhan/whisper-base-hawrami-transcription", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16747c57a48c53b4a8c276247b86e94504d72c17ec9ffeb1c3358ba2a7541730
- Size of remote file:
- 5.5 kB
- SHA256:
- b07b7a9cccf4a5c9e267b6d53a140cbce99876f03236ec74446bf9d6fa7ceaca
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