Automatic Speech Recognition
Transformers
Safetensors
cohere_asr
audio
speech-recognition
transcription
diarization
speaker-diarization
timestamps
custom_code
Instructions to use syvai/cohere-transcribe-diarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syvai/cohere-transcribe-diarize with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="syvai/cohere-transcribe-diarize", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("syvai/cohere-transcribe-diarize", trust_remote_code=True) model = AutoModelForSpeechSeq2Seq.from_pretrained("syvai/cohere-transcribe-diarize", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Need for clarification
#1
by AccidentalMVP - opened
when hosting this model via vLLM
is it able to process audio > 30sec ?
and if so is it limited to a specific duration?
trained for 30 secs max. might do a little higher.
mhenrichsen changed discussion status to closed