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examples/tts/README-csm.md

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# Sesame CSM
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This demo shows running inference of [Sesame CSM](https://github.com/SesameAILabs/csm) using llama.cpp / GGML
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It contains 3 components (each has its own GGUF file):
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1. Backbone LLM
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2. Decoder LLM
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3. Mimi decoder
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## Quick start
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By default, all GGUF files are downloaded from [ggml-org Hugging Face's account](https://huggingface.co/ggml-org/sesame-csm-1b-GGUF)
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```sh
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# build (make sure to have LLAMA_CURL enabled)
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cmake -B build -DLLAMA_CURL=ON
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cmake --build build -j --target llama-tts-csm
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# run it
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./build/bin/llama-tts-csm -p "[0]Hi, my name is Xuan Son. I am software engineer at Hugging Face."
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```
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## Convert the model yourself
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To get the GGUF:
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```sh
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python examples/tts/convert_csm_to_gguf.py --outtype q8_0
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```
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Compile the example:
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```sh
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cmake --build build -j --target llama-tts-csm
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```
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Run the example:
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Run the example using local file:
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```sh
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./build/bin/llama-tts-csm -m sesame-csm-backbone.gguf -p "[0]Hello world."
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./build/bin/llama-tts-csm -m sesame-csm-backbone.gguf -mv kyutai-mimi.gguf -p "[0]Hello world."
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# sesame-csm-backbone.gguf will automatically be loaded
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# make sure the place these 2 GGUF files in the same directory
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