huggingface--transformers/docs/source/en/model_doc/cohere_asr.md

This model was contributed to Hugging Face Transformers on 2026-03-26.

CohereAsr

Overview

Cohere ASR, released by Cohere on March 26th, 2026, is a 2B parameter Conformer-based encoder-decoder speech recognition model.

This model was contributed by Eustache Le Bihan.

Usage

Short-form transcription

from transformers import AutoProcessor, CohereAsrForConditionalGeneration
from transformers.audio_utils import load_audio


revision = "refs/pr/6"
processor = AutoProcessor.from_pretrained("CohereLabs/cohere-transcribe-03-2026", revision=revision)
model = CohereAsrForConditionalGeneration.from_pretrained("CohereLabs/cohere-transcribe-03-2026", device_map="auto", revision=revision)

audio = load_audio(
    "https://huggingface.co/datasets/hf-internal-testing/dummy-audio-samples/resolve/main/bcn_weather.mp3",
    sampling_rate=16000,
)

inputs = processor(audio, sampling_rate=16000, return_tensors="pt", language="en").to(model.device)
inputs.to(model.device, dtype=model.dtype)

outputs = model.generate(**inputs, max_new_tokens=256)
text = processor.decode(outputs, skip_special_tokens=True)
print(text)

Punctuation control

Pass punctuation=False to obtain lower-cased output without punctuation marks.

inputs_pnc = processor(audio, sampling_rate=16000, return_tensors="pt", language="en", punctuation=True).to(model.device)
inputs_nopnc = processor(audio, sampling_rate=16000, return_tensors="pt", language="en", punctuation=False).to(model.device)

Long-form transcription

For audio longer than the feature extractor's max_audio_clip_s, the feature extractor automatically splits the waveform into chunks. The processor reassembles the per-chunk transcriptions using the returned audio_chunk_index.

audio_long = load_audio(
    "https://huggingface.co/datasets/hf-internal-testing/dummy-audio-samples/resolve/main/obama_first_45_secs.mp3",
    sampling_rate=16000,
)

inputs = processor(audio=audio_long, return_tensors="pt", language="en", sampling_rate=16000).to(model.device)
audio_chunk_index = inputs.get("audio_chunk_index")
inputs.to(model.device, dtype=model.dtype)

outputs = model.generate(**inputs, max_new_tokens=256)
text = processor.decode(outputs, skip_special_tokens=True, audio_chunk_index=audio_chunk_index, language="en")
print(text)

Batched inference

Multiple audio files can be processed in a single call. When the batch mixes short-form and long-form audio, the processor handles chunking and reassembly.

audio_short = load_audio(
    "https://huggingface.co/datasets/hf-internal-testing/dummy-audio-samples/resolve/main/bcn_weather.mp3",
    sampling_rate=16000,
)
audio_long = load_audio(
    "https://huggingface.co/datasets/hf-internal-testing/dummy-audio-samples/resolve/main/obama_first_45_secs.mp3",
    sampling_rate=16000,
)

inputs = processor([audio_short, audio_long], sampling_rate=16000, return_tensors="pt", language="en").to(model.device)
audio_chunk_index = inputs.get("audio_chunk_index")
inputs.to(model.device, dtype=model.dtype)

outputs = model.generate(**inputs, max_new_tokens=256)
text = processor.decode(
    outputs, skip_special_tokens=True, audio_chunk_index=audio_chunk_index, language="en"
)
print(text)

Non-English transcription

Specify the language code to transcribe in any of the 14 supported languages.

audio_es = load_audio(
    "https://huggingface.co/datasets/hf-internal-testing/dummy-audio-samples/resolve/main/fleur_es_sample.wav",
    sampling_rate=16000,
)

inputs = processor(audio_es, sampling_rate=16000, return_tensors="pt", language="es", punctuation=True).to(model.device)
inputs.to(model.device, dtype=model.dtype)

outputs = model.generate(**inputs, max_new_tokens=256)
text = processor.decode(outputs, skip_special_tokens=True)
print(text)

CohereAsrConfig

autodoc CohereAsrConfig

CohereAsrFeatureExtractor

autodoc CohereAsrFeatureExtractor - call

CohereAsrProcessor

autodoc CohereAsrProcessor - call

CohereAsrPreTrainedModel

autodoc CohereAsrPreTrainedModel - forward

CohereAsrModel

autodoc CohereAsrModel - forward

CohereAsrForConditionalGeneration

autodoc CohereAsrForConditionalGeneration - forward