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)# 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
Prompt engineering for word boosting
#43
by syafie-nzm - opened
i am evaluating cohere transcribe model for medical use case, i wonder if cohere model can do context injection or initial prompting for boosting specific words or context.
if this feature is already there, may you point to me how to do that. If not, will it be in your future roadmap?
Thanks