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Update Model URLs + Notification about PyTorch versions (#2)

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- Update Model URLs + Notification about PyTorch versions (aeca22251969b848517a22fee5a5ccd626f083e8)

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  1. README.md +9 -7
README.md CHANGED
@@ -3,6 +3,7 @@ inference: false
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  tags:
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  - SeamlessM4T
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  license: cc-by-nc-4.0
 
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  ---
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  # SeamlessM4T - On-Device
@@ -10,21 +11,22 @@ 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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  Apart from [SeamlessM4T-LARGE (2.3B)](https://huggingface.co/facebook/seamless-m4t-large) and [SeamlessM4T-MEDIUM (1.2B)](https://huggingface.co/facebook/seamless-m4t-medium) models, we are also developing a small model (281M) targeting for on-device inference. [This folder]((https://huggingface.co/facebook/seamless-m4t-unity-small-s2t)) contains an example to run an exported small model covering ASR and S2TT. The model could be executed on popular mobile devices with Pytorch Mobile (https://pytorch.org/mobile/home/).
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  Refer to [UnitY-Small](https://huggingface.co/facebook/seamless-m4t-unity-small) if you also wish to cover speech-to-speech translation (S2ST) in addition to ASR and S2TT tasks.
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  ## Overview
 
 
 
 
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- | Model | Disk Size | Supported Tasks | Supported Languages|
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- |---------|----------------------|-------------------------|-------------------------|
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- | [UnitY-Small](https://huggingface.co/facebook/seamless-m4t-unity-small/resolve/main/unity_on_device.ptl) | 862MB | S2ST, S2TT, ASR |eng, fra, hin, por, spa|
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- | [UnitY-Small-S2T](https://huggingface.co/facebook/seamless-m4t-unity-small-s2t/resolve/main/unity_on_device_s2t.ptl) | 637MB | S2TT, ASR |eng, fra, hin, por, spa|
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- [UnitY-Small-S2T](https://huggingface.co/facebook/seamless-m4t-unity-small-s2t) is a pruned version of [UnitY-Small](https://huggingface.co/facebook/seamless-m4t-unity-small) without 2nd pass unit decoding. Unlike [UnitY-Small](https://huggingface.co/facebook/seamless-m4t-unity-small), it can only be used for ASR and S2TT tasks.
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  ## Inference
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  To use exported model, users don't need seamless_communication or fairseq2 dependency.
 
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  tags:
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  - SeamlessM4T
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  license: cc-by-nc-4.0
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+ library_name: fairseq2
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  ---
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  # SeamlessM4T - On-Device
 
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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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  Apart from [SeamlessM4T-LARGE (2.3B)](https://huggingface.co/facebook/seamless-m4t-large) and [SeamlessM4T-MEDIUM (1.2B)](https://huggingface.co/facebook/seamless-m4t-medium) models, we are also developing a small model (281M) targeting for on-device inference. [This folder]((https://huggingface.co/facebook/seamless-m4t-unity-small-s2t)) contains an example to run an exported small model covering ASR and S2TT. The model could be executed on popular mobile devices with Pytorch Mobile (https://pytorch.org/mobile/home/).
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  Refer to [UnitY-Small](https://huggingface.co/facebook/seamless-m4t-unity-small) if you also wish to cover speech-to-speech translation (S2ST) in addition to ASR and S2TT tasks.
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  ## Overview
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+ | Model | Checkpoint | Num Params | Disk Size | Supported Tasks | Supported Languages|
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+ |---------|------------|----------|-------------|------------|-------------------------|
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+ | UnitY-Small|[🤗 Model card](https://huggingface.co/facebook/seamless-m4t-unity-small) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-unity-small/resolve/main/unity_on_device.ptl) | 281M | 862MB | S2ST, S2TT, ASR |eng, fra, hin, por, spa|
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+ | UnitY-Small-S2T |[🤗 Model card](https://huggingface.co/facebook/seamless-m4t-unity-small-s2t) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-unity-small-s2t/resolve/main/unity_on_device_s2t.ptl) | 235M | 637MB | S2TT, ASR |eng, fra,hin, por, spa|
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+ UnitY-Small-S2T is a pruned version of UnitY-Small without 2nd pass unit decoding.
 
 
 
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+ Note: If using pytorch runtime in python, only **pytorch<=1.11.0** is supported for **UnitY-Small(281M)**. We tested UnitY-Small-S2T(235M), it works with later versions.
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  ## Inference
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  To use exported model, users don't need seamless_communication or fairseq2 dependency.