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docs: update README.md (#735)

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streaminig -> streaming
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Ikko Eltociear Ashimine
2025-01-17 01:30:32 +09:00
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@@ -136,7 +136,7 @@ MiniCPM-o 2.6 can be easily used in various ways: (1) [llama.cpp](https://github
**Model Architecture.**
- **End-to-end Omni-modal Architecture.** Different modality encoder/decoders are connected and trained in an **end-to-end** fashion to fully exploit rich multimodal knowledge. The model is trained in a fully end-to-end manner with only CE loss.
- **Omni-modal Live Streaming Mechanism.** (1) We change the offline modality encoder/decoders into online ones for **streaminig inputs/outputs.** (2) We devise a **time-division multiplexing (TDM) mechanism** for omni-modality streaminig processing in the LLM backbone. It divides parallel omni-modality streams into sequential info within small periodic time slices.
- **Omni-modal Live Streaming Mechanism.** (1) We change the offline modality encoder/decoders into online ones for **streaming inputs/outputs.** (2) We devise a **time-division multiplexing (TDM) mechanism** for omni-modality streaming processing in the LLM backbone. It divides parallel omni-modality streams into sequential info within small periodic time slices.
- **Configurable Speech Modeling Design.** We devise a multimodal system prompt, including traditional text system prompt, and **a new audio system prompt to determine the assistant voice**. This enables flexible voice configurations in inference time, and also facilitates end-to-end voice cloning and description-based voice creation.
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