mms-cclms
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mms-lid-1024
facebookThis checkpoint is a model fine-tuned for speech language identification (LID) and part of Facebook's Massive Multilingual Speech project. This checkpoint is based on the Wav2Vec2 architecture and classifies raw audio input to a probability distribution over 1024 output classes (each class representing a language). The checkpoint consists of **1 billion parameters** and has been fine-tuned from facebook/mms-1b on 1024 languages. - Example - Supported Languages - Model details - Additional links This MMS checkpoint can be used with Transformers to identify the spoken language of an audio. It can recognize the following 1024 languages.
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View details ↗mms-lid-126
facebookThis checkpoint is a model fine-tuned for speech language identification (LID) and part of Facebook's Massive Multilingual Speech project. This checkpoint is based on the Wav2Vec2 architecture and classifies raw audio input to a probability distribution over 126 output classes (each class representing a language). The checkpoint consists of **1 billion parameters** and has been fine-tuned from facebook/mms-1b on 126 languages. This MMS checkpoint can be used with Transformers to identify the spoken language of an audio. It can recognize the following 126 languages. **Note**: In order to use MMS you need to have at least `transformers >= 4.30` installed. If the `4.30` version is not yet available on PyPI make sure to install `transformers` from source:
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View details ↗mms-lid-2048
facebookThis checkpoint is a model fine-tuned for speech language identification (LID) and part of Facebook's Massive Multilingual Speech project. This checkpoint is based on the Wav2Vec2 architecture and classifies raw audio input to a probability distribution over 2048 output classes (each class representing a language). The checkpoint consists of **1 billion parameters** and has been fine-tuned from facebook/mms-1b on 2048 languages. This MMS checkpoint can be used with Transformers to identify the spoken language of an audio. It can recognize the following 2048 languages. **Note**: In order to use MMS you need to have at least `transformers >= 4.30` installed. If the `4.30` version is not yet available on PyPI make sure to install `transformers` from source:
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View details ↗mms-lid-256
facebookThis checkpoint is a model fine-tuned for speech language identification (LID) and part of Facebook's Massive Multilingual Speech project. This checkpoint is based on the Wav2Vec2 architecture and classifies raw audio input to a probability distribution over 256 output classes (each class representing a language). The checkpoint consists of **1 billion parameters** and has been fine-tuned from facebook/mms-1b on 256 languages. - Example - Supported Languages - Model details - Additional links This MMS checkpoint can be used with Transformers to identify the spoken language of an audio. It can recognize the following 256 languages.
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View details ↗mms-lid-4017
facebookThis checkpoint is a model fine-tuned for speech language identification (LID) and part of Facebook's Massive Multilingual Speech project. This checkpoint is based on the Wav2Vec2 architecture and classifies raw audio input to a probability distribution over 4017 output classes (each class representing a language). The checkpoint consists of **1 billion parameters** and has been fine-tuned from facebook/mms-1b on 4017 languages. - Example - Supported Languages - Model details - Additional links This MMS checkpoint can be used with Transformers to identify the spoken language of an audio. It can recognize the following 4017 languages.
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View details ↗mms-lid-512
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View details ↗mms-tts
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View details ↗mms-tts-abi
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View details ↗mms-tts-abp
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View details ↗mms-tts-aca
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View details ↗mms-tts-acd
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View details ↗mms-tts-ace
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View details ↗mms-tts-acf
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View details ↗mms-tts-ach
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View details ↗mms-tts-acn
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View details ↗mms-tts-acr
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View details ↗mms-tts-acu
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View details ↗mms-tts-ade
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View details ↗mms-tts-adh
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View details ↗mms-tts-adj
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View details ↗mms-tts-adx
facebook基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗mms-tts-aeu
facebook基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗mms-tts-agd
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