Instructions to use seba3y/whisper-large-v2-16fp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seba3y/whisper-large-v2-16fp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="seba3y/whisper-large-v2-16fp")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("seba3y/whisper-large-v2-16fp") model = AutoModelForSpeechSeq2Seq.from_pretrained("seba3y/whisper-large-v2-16fp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03725a96c31702b1126f4a9f82e162ff2955af352047d22fa9e62f2e45a227da
- Size of remote file:
- 3.09 GB
- SHA256:
- 691684065f488fe829b25ab94a14d36364ac9ac0bb08d2279709954b79871838
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