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README.md
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If not already stored in your system, the SeamlessM4T model will be downloaded automatically when
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running the script. The output will be saved in `${OUT_DIR}`.
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We suggest
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any device (e.g., CPU) supported by SimulEval and HuggingFace.
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## 💬 Inference using docker
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To run SimulSeamless using docker,
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steps below:
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1. Download the docker file by cloning this repository
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2. Load the docker image:
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```bash
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```
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To set, `${TGT_LANG}`, `${FRAME}`, `${LAYER}`, `${BLEU_TOKENIZER}`, `${LATENCY_UNIT}`,
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`${LIST_OF_AUDIO}`, `${TGT_FILE}`, `${SEG_SIZE}`, and `${OUT_DIR}` refer to
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[🤖 Inference using your environment](
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## 📍Citation
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If not already stored in your system, the SeamlessM4T model will be downloaded automatically when
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running the script. The output will be saved in `${OUT_DIR}`.
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We suggest running the inference using a GPU to speed up the process but the system can be run on
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any device (e.g., CPU) supported by SimulEval and HuggingFace.
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## 💬 Inference using docker
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+
To run SimulSeamless using docker, follow the steps below:
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1. Download the docker file by cloning this repository
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2. Load the docker image:
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```bash
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```
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To set, `${TGT_LANG}`, `${FRAME}`, `${LAYER}`, `${BLEU_TOKENIZER}`, `${LATENCY_UNIT}`,
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`${LIST_OF_AUDIO}`, `${TGT_FILE}`, `${SEG_SIZE}`, and `${OUT_DIR}` refer to
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[🤖 Inference using your environment](#🤖-inference-using-your-environment).
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## 📍Citation
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