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Fixes for the notebook.

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laurent 2025-07-03 13:05:00 +02:00
parent 1cd9529f65
commit 25574aa104
2 changed files with 3 additions and 2 deletions
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2
README.md
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@ -52,7 +52,7 @@ Here is how to choose which one to use:
<a href="https://huggingface.co/kyutai/stt-2.6b-en" target="_blank" style="margin: 2px;"> <a href="https://huggingface.co/kyutai/stt-2.6b-en" target="_blank" style="margin: 2px;">
<img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue" style="display: inline-block; vertical-align: middle;"/> <img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue" style="display: inline-block; vertical-align: middle;"/>
</a> </a>
<a target="_blank" href="https://colab.research.google.com/github/kyutai-labs/delayed-streams-modeling/blob/main/stt_pytorch.ipynb"> <a target="_blank" href="https://colab.research.google.com/github/kyutai-labs/delayed-streams-modeling/blob/main/tts_pytorch.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a> </a>

3
tts_pytorch.ipynb
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@ -7,7 +7,7 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"!pip install git+https://git@github.com/kyutai-labs/moshi#egg=moshi&subdirectory=moshi" "!pip install \"git+https://git@github.com/kyutai-labs/moshi#egg=moshi&subdirectory=moshi\""
] ]
}, },
{ {
@ -54,6 +54,7 @@
"tts_model = TTSModel.from_checkpoint_info(\n", "tts_model = TTSModel.from_checkpoint_info(\n",
" checkpoint_info, n_q=32, temp=0.6, device=torch.device(\"cuda\"), dtype=torch.half\n", " checkpoint_info, n_q=32, temp=0.6, device=torch.device(\"cuda\"), dtype=torch.half\n",
")\n", ")\n",
"tts_model.mimi.streaming_forever(1)\n",
"\n", "\n",
"# You could also generate multiple audios at once by passing a list of texts.\n", "# You could also generate multiple audios at once by passing a list of texts.\n",
"entries = tts_model.prepare_script([text], padding_between=1)\n", "entries = tts_model.prepare_script([text], padding_between=1)\n",