Instructions to use mkrausio/EmoWhisper-Bursts-Small-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkrausio/EmoWhisper-Bursts-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-Bursts-Small-v0.1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mkrausio/EmoWhisper-Bursts-Small-v0.1") model = AutoModelForSpeechSeq2Seq.from_pretrained("mkrausio/EmoWhisper-Bursts-Small-v0.1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56686a21ca8e98241f21056b46ba585f209762cc710a98d96c3f605f67314c5d
- Size of remote file:
- 967 MB
- SHA256:
- 00befafb5266247f1b9487ecf23b3a205fd9a6e464eb43a35489b2626ee00c76
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