Cohere Transcribe Mlx FP16

Integrity

model.safetensors sha256 dab83b01ee41b929f2f644aa9ecb388db1359f9f7e1d6db64b6c35def30ab9ba

Use with mlx-audio

python -m mlx_audio.stt.generate --model littoralai/cohere-transcribe-mlx-fp16 \
  --audio audio.wav --output out

--- library_name: mlx tags: - mlx - automatic-speech-recognition - audio - speech-recognition - transcription - cohere_asr - custom_code language: - multilingual license: apache-2.0 pipeline_tag: automatic-speech-recognition base_model: CohereLabs/cohere-transcribe-03-2026 base_model_relation: quantized --- # littoralai/cohere-transcribe-mlx-fp16 fp16 MLX conversion of [CohereLabs/cohere-transcribe-03-2026](https://huggingface.co/CohereLabs/cohere-transcribe-03-2026) (source revision `b1eacc2686a3d08ceaae5f24a88b1d519620bc09`), converted with mlx-audio. No architecture, vocabulary, or training changes. See the base model card for capabilities, training details, and evaluations. ## License Apache-2.0, from the base model. The custom architecture code (`modeling_cohere_asr.py`, `configuration_cohere_asr.py`, `processing_cohere_asr.py`, `tokenization_cohere_asr.py`) is Cohere's, redistributed unchanged. Change vs. the source: fp16 MLX conversion. ## Integrity `model.safetensors` sha256 `dab83b01ee41b929f2f644aa9ecb388db1359f9f7e1d6db64b6c35def30ab9ba` ## Use with mlx-audio ```bash python -m mlx_audio.stt.generate --model littoralai/cohere-transcribe-mlx-fp16 \ --audio audio.wav --output out ```