Instructions to use razhan/whisper-small-me with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razhan/whisper-small-me with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="razhan/whisper-small-me")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("razhan/whisper-small-me") model = AutoModelForSpeechSeq2Seq.from_pretrained("razhan/whisper-small-me", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6bb188c96b369e0cff947690bddb3a9a7c5d2a5042a098be638a9040b95e664
- Size of remote file:
- 5.5 kB
- SHA256:
- 9a20498dfb4f18f74c30bdf777103c418d4061c9f3ab3bc3612094001b45a0d1
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