Automatic Speech Recognition
Transformers
OpenVINO
audio
hf-asr-leaderboard
speech-recognition
transcription
Instructions to use Aditya02/cohere-transcribe-03-2026-ov-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aditya02/cohere-transcribe-03-2026-ov-fp16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Aditya02/cohere-transcribe-03-2026-ov-fp16")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Aditya02/cohere-transcribe-03-2026-ov-fp16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
README.md
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# Cohere Transcribe OpenVINO
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This repository contains an **OpenVINO™ IR** version of
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The repository includes everything required to run inference with OpenVINO, including the model IR files, tokenizer, processor configuration, and metadata.
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# Cohere Transcribe OpenVINO
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This repository contains an **OpenVINO™ IR** version of Cohere Transcribe optimized for efficient inference with the OpenVINO Runtime. The model has been exported into separate **encoder**, **decoder**, and **decoder-with-past** graphs to enable fast autoregressive decoding using KV-cache.
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The repository includes everything required to run inference with OpenVINO, including the model IR files, tokenizer, processor configuration, and metadata.
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