Instructions to use nyralabs/CrisperWhisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyralabs/CrisperWhisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nyralabs/CrisperWhisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("nyralabs/CrisperWhisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("nyralabs/CrisperWhisper") - Notebooks
- Google Colab
- Kaggle
Support for Italian language?
Hello, I was using this model last month for transcribing Italian speech and it was working fine.
Today I was checking the hugging face repo and it says that it supports just German and English and I am bit confused.
Has it always been only for two languages?
Since it was only finetuned on English and German Data performance and verbatimness is likely better in these languages. If you however observe that it works well in italian too that makes me very happy. It would mean that these capabilities and the retokenization seem to (atleast partly) transfer to other languages too even tough the model has not specifically been trained on languages other than english and german after the retokenization.
thank you for the clarification!