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Hi Moonshot team,

Thank you for providing this amazing model.
I have tried starting kimi-audio-7b with docker, and here is my walkthrough. Please kindly review and feel free to merge. Thank you so much 😄

Signed-off-by: tunglinwood <tomwu.tunglin@gmail.com>
@AlanSwift AlanSwift requested a review from MoyanZitto April 28, 2025 14:37
@MoyanZitto
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MoyanZitto commented Apr 29, 2025

@tunglinwood Thank you for your interest in our project. This PR adds more instructions that should be noticed by users, but I think it contains too many details. Here are my suggestions:

  • Skip the explanations and verifications, and merge the key actions for preparing the environment into the "Quick Start" section (e.g., git clone --recurse-submodules, cd ..).
  • For Docker, there are two things users might miss, so I think it would be helpful to include a section before "Quick Start":
    • We have a pre-built Docker image available: docker pull moonshotai/kimi-audio:v0.1. (which is documented in huggingface repo but not here )
    • You may need to mount your local directory to access the cloned repository, and you need to use --gpus to enable GPU support (i.e., in your Docker command).
  • You don't need to manually download the Hugging Face model and pass the local path. Just use the model_id, pls verify this.

…with little modification.

Signed-off-by: tomwu.tunglin@gmail.com <tomwu.tunglin@gmail.com>
@tunglinwood
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Hi, @MoyanZitto I have updated the pull, please kindly review.

@tunglinwood
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@MoyanZitto Hello could you kindly help to review the pull?


## Quick Start

### 1. Inference with Docker
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Suggested change
### 1. Inference with Docker
### 1. Set environment

- [Introduction](#introduction)
- [Architecture Overview](#architecture-overview)
- [Quick Start](#quick-start)
- [1. Inference with Docker](#1-inference-with-docker)
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Suggested change
- [1. Inference with Docker](#1-inference-with-docker)
- [1. Set environment](#1-set-environment)


### 1. Inference with Docker

We recommend that you build a Docker image to run the inference. You can construct the image using the `docker build` command.
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I believe we can reorganize readme:

  • get code ( note you need submodule update --init)
  • set envrionment
    • use pre-built image ( we should prefer this because it's simpler)
    • build your own image
  • run demo
    • i.e inference with python

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2 participants