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@@ -10,8 +10,8 @@ SeamlessM4T is designed to provide high quality translation, allowing people fro
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  SeamlessM4T covers:
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  - 📥 101 languages for speech input
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- - ⌨️ 96 Languages for text input/output
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- - 🗣️ 35 languages for speech output.
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  This unified model enables multiple tasks without relying on multiple separate models:
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  - Speech-to-speech translation (S2ST)
@@ -23,13 +23,15 @@ This unified model enables multiple tasks without relying on multiple separate m
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  ## SeamlessM4T models
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  | Model Name | #params | checkpoint | metrics |
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  | - | - | - | - |
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- | SeamlessM4T-Large | 2.3B |[model]() | [metrics]() |
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- | SeamlessM4T-Medium | 1.2B |[model]() | [metrics]() |
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  We provide the extensive evaluation results of seamlessM4T-Large and SeamlessM4T-Medium reported in the paper (as averages) in the `metrics` files above.
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  ## Instructions to run inference with SeamlessM4T models
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  Inference calls for the `Translator` object instanciated with a Multitasking UnitY model with the options:
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  - `multitask_unity_large`
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  - `multitask_unity_medium`
 
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  SeamlessM4T covers:
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  - 📥 101 languages for speech input
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+ - ⌨️ 96 Languages for text input/output
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+ - 🗣️ 35 languages for speech output.
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  This unified model enables multiple tasks without relying on multiple separate models:
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  - Speech-to-speech translation (S2ST)
 
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  ## SeamlessM4T models
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  | Model Name | #params | checkpoint | metrics |
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  | - | - | - | - |
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+ | SeamlessM4T-Large | 2.3B |[🤗 Model card](https://huggingface.co/facebook/seamless-m4t-large) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-large/resolve/main/multitask_unity_large.pt) | [metrics]() |
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+ | SeamlessM4T-Medium | 1.2B |[🤗 Model card](https://huggingface.co/facebook/seamless-m4t-medium) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-medium/resolve/main/multitask_unity_medium.pt) | [metrics]() |
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  We provide the extensive evaluation results of seamlessM4T-Large and SeamlessM4T-Medium reported in the paper (as averages) in the `metrics` files above.
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  ## Instructions to run inference with SeamlessM4T models
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+ Install `seamless_communication` by following the instructions mentioned here: [Installation](https://github.com/fairinternal/seamless_communication/tree/main#installation)
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+
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  Inference calls for the `Translator` object instanciated with a Multitasking UnitY model with the options:
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  - `multitask_unity_large`
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  - `multitask_unity_medium`