Instructions to use mkrausio/EmoWhisper-Snp-Small-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkrausio/EmoWhisper-Snp-Small-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mkrausio/EmoWhisper-Snp-Small-v0.1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mkrausio/EmoWhisper-Snp-Small-v0.1") model = AutoModelForSpeechSeq2Seq.from_pretrained("mkrausio/EmoWhisper-Snp-Small-v0.1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80f4b421225d82e6545c0193a5a8a1d019be967c9c365a86d880aa5695db8bce
- Size of remote file:
- 967 MB
- SHA256:
- f9d1d4a4f63be1a39cb22bb665ab30104238d3561513c167ecc0f519784b8746
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