SesameAILabs/csm

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

14728 stars · 1479 forks observed · 2026-09-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

CSM (Conversational Speech Model) is Sesame's speech generation model that produces conversational audio from text and audio context, using a Llama backbone with a Mimi audio decoder. The repository provides Python code for loading the 1B checkpoint and generating speech, including context-aware multi-speaker conversations.

Use cases

• generate natural-sounding speech from text
• build a conversational voice assistant
• create multi-speaker dialogue audio with context prompts
• clone speaker identity from audio context segments
• integrate TTS into Python applications via Hugging Face Transformers

When to choose

• you need context-aware, conversational-quality speech generation
• you have a CUDA GPU and want a Python API for TTS
• you want an open-weights 1B speech model with Llama backbone

When to avoid

• you need production TTS without GPU hardware
• you need non-English speech or fine-grained voice control beyond context prompting
• you need a lightweight CPU-only text-to-speech solution

Facets

library · maturity active

tts speech-recognition machine-learning deep-learning llm-inference speech-processing artificial-intelligence large-language-models python windows conversational-speech voice-generation llama-backbone rvq-audio-codes mimi-codec huggingface audio gpu linux macos

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markdown · JSON · MCP: product_card(name="SesameAILabs/csm")