Automatic Speech Recognition
Transformers
Safetensors
cohere_asr
audio
hf-asr-leaderboard
speech-recognition
transcription
custom_code
Eval Results
Instructions to use CohereLabs/cohere-transcribe-03-2026 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CohereLabs/cohere-transcribe-03-2026 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="CohereLabs/cohere-transcribe-03-2026", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("CohereLabs/cohere-transcribe-03-2026", trust_remote_code=True) model = AutoModelForSpeechSeq2Seq.from_pretrained("CohereLabs/cohere-transcribe-03-2026", trust_remote_code=True, device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Fix: avoid passing None decoder_attention_mask to generation_kwargs
#35
by vamsin07 - opened
Thanks for this but we haven't tested this generate( + trust_remote_code=True code path. We will continue to fix bugs in the trust_remote_code=True path that are surfaced when running according to the original docs but we don't intend to widen the API surface for the deprecated version as it has the chance to break people's existing workflows using that code path.
See here for context: https://huggingface.co/CohereLabs/cohere-transcribe-03-2026/discussions/34#69e5f33b73519ae4cc18199a
Thanks again!
julianmack changed pull request status to closed