Instructions to use danielrosehill/daniel_whisper_finetune_small_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielrosehill/daniel_whisper_finetune_small_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="danielrosehill/daniel_whisper_finetune_small_v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("danielrosehill/daniel_whisper_finetune_small_v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("danielrosehill/daniel_whisper_finetune_small_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c31f5bc952ed070eccf4ba035bd9e4159703364122606f06009abf827bc23ea8
- Size of remote file:
- 6.03 kB
- SHA256:
- 2287318b9b7531f6703857abffbd9749e7071ac9e43ec735329829dd33bb7d32
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