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README.md
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- covost2
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- europarl_st
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- voxpopuli
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- example_title: Common Voice sample 1
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src: https://huggingface.co/facebook/xm_transformer_600m-es_en-multi_domain/resolve/main/common_voice_es_19966634.flac
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---
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##
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Speech-to-speech translation model from fairseq S2UT ([paper](https://arxiv.org/abs/2204.02967)/[code](https://github.com/facebookresearch/fairseq/blob/main/examples/speech_to_speech/docs/enhanced_direct_s2st_discrete_units.md)):
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- Trained on mTEDx, CoVoST 2, Europarl-ST and VoxPopuli
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- Speech synthesis with [facebook/
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## Usage
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```python
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cache_dir = os.getenv("HUGGINGFACE_HUB_CACHE")
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models, cfg, task = load_model_ensemble_and_task_from_hf_hub(
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"facebook/
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arg_overrides={"config_yaml": "config.yaml", "task": "speech_to_text"},
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cache_dir=cache_dir,
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)
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cache_dir or (Path.home() / ".cache" / library_name).as_posix()
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cache_dir = snapshot_download(
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f"facebook/
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)
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x = hub_utils.from_pretrained(
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- covost2
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- europarl_st
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- voxpopuli
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---
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## xm_transformer_s2ut_en-hk
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Speech-to-speech translation model from fairseq S2UT ([paper](https://arxiv.org/abs/2204.02967)/[code](https://github.com/facebookresearch/fairseq/blob/main/examples/speech_to_speech/docs/enhanced_direct_s2st_discrete_units.md)):
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- English-Hokkien
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- Trained on mTEDx, CoVoST 2, Europarl-ST and VoxPopuli
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- Speech synthesis with [facebook/unit_hifigan_HK_layer12.km2500_frame_TAT-TTS](https://huggingface.co/facebook/unit_hifigan_HK_layer12.km2500_frame_TAT-TTS)
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## Usage
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```python
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cache_dir = os.getenv("HUGGINGFACE_HUB_CACHE")
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models, cfg, task = load_model_ensemble_and_task_from_hf_hub(
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"facebook/xm_transformer_s2ut_en-hk",
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arg_overrides={"config_yaml": "config.yaml", "task": "speech_to_text"},
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cache_dir=cache_dir,
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)
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cache_dir or (Path.home() / ".cache" / library_name).as_posix()
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)
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cache_dir = snapshot_download(
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f"facebook/unit_hifigan_HK_layer12.km2500_frame_TAT-TTS", cache_dir=cache_dir, library_name=library_name
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)
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x = hub_utils.from_pretrained(
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