Automatic Speech Recognition
Transformers
Safetensors
DiCoW
speech
whisper
multilingual
speaker-diarization
meeting-transcription
BUT-FIT
custom_code
Instructions to use BUT-FIT/DiCoW_v3_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUT-FIT/DiCoW_v3_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BUT-FIT/DiCoW_v3_2", trust_remote_code=True)# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("BUT-FIT/DiCoW_v3_2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Original SE_DiCoW model missing from huggingface
#1
by taavi223 - opened
Hi! I noticed that the BUT-FIT/SE_DiCoW (underscore) model has been "replaced" with a new BUT-FIT/SE-DiCoW (hyphen) model, but the new model requires a different version of the github.com/BUTSpeechFIT/DiCoW repo to run.
Is it possible to make the old model available again? I'd like to be able to continue using the original BUT-FIT/SE_DiCoW model without having to update all my harness code to work with the new model.
Thanks for releasing these models!
Hi,
sure, I made it public again.
Best,
Alex