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OneInfer

Inference model all in one. Easily Large Model Inference on Your Local Machine.

A lightweight CLI tool that simplifies deploying and managing machine learning models locally. Designed for seamless integration of popular model sources (Hugging Face Hub, ModelScope, local files) with optimized CPU/GPU execution via llama.cpp backend (more backends coming soon).

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Difference from Ollama

Compared to Ollama, OneInfer offers more flexibility and choices:

  1. Broader model platform support: OneInfer supports downloading models from multiple platforms, including Hugging Face and ModelScope, whereas Ollama is limited to its platform.
  2. Support for diverse inference backends: OneInfer will support various inference backends, not only for language models but also for visual models and other non-LLM models, providing users with more options and freedom.

With OneInfer, users can enjoy the convenience of portable local deployment while benefiting from more platform and model choices, offering a richer and more flexible experience.

Roadmap

  • Ollama-like model management
  • Using any pre-trained models from Hugging Face or ModelScope
  • Support for serving LLM models using llama.cpp (.gguf models)
  • Web UI
  • Ready-to-use packaged application, allowing users to download and use it immediately without the need for compilation.
  • More inference backends to be supported
  • More types of models to be supported

Requirements

  • Python3 for downloading models from Hugging Face and ModelScope.
  • Go 1.18+ for building oneinfer.
  • git for downloading other repos.

Install pre-built Package

Checkout https://github.com/derekwin/OneInfer/releases and install oneinfer by following the instructions provided.

Build and Install

To build and install OneInfer:

  1. Clone the repository:

    git clone https://github.com/derekwin/oneinfer.git
cd oneinfer

  2. Run the make command:

    make USE_CUDA=1

    for different GPU/backend:

    • USE_BLAS=1: For general CPU usage.
    • USE_CUDA=1: For NVIDIA GPUs.
    • USE_MUSA=1: For Meta's AI accelerators.
    • USE_HIP=1: For AMD GPUs.
    • USE_CANN=1: For Huawei Ascend AI accelerators.
    • USE_Vulkan=1: For GPUs that support Vulkan, offering efficient parallel computation.
    • USE_Metal=1: For Apple devices.
    • USE_SYCL=1: For a variety of heterogeneous devices (including CPU, GPU, FPGA) using oneAPI.

  3. Install/Uninstall the binary:

    sudo bash install.sh/uninstall.sh

or you can run bash allinnoe.sh directly.

Usage

model add

Add a model to OneInfer. This can either be from ModelScope, Hugging Face, or a local file. (You can get repo name and file name from huggingface or modelscope website.)

oneinfer add <model_repo> <platform_name> <file_name>

Download a model from ModelScope

Example for downloading the DeepSeek model from ModelScope:

# deepseek r1 from unsloth
oneinfer add unsloth/DeepSeek-R1-Distill-Qwen-32B-GGUF modelscope DeepSeek-R1-Distill-Qwen-32B-Q5_K_M.gguf
oneinfer add unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF modelscope DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf

Download a model from Hugging Face

Example for downloading a model from Hugging Face:

oneinfer add RepoId huggingface modelname

Add a local model

Example for adding a local model file:

oneinfer add localmodelname local 
# then type file path
./test/fakemodel.bin

model list

List all available models that have been added to OneInfer.

oneinfer ls

model remove

Remove a specific model by its name.

oneinfer rm <model_name>

Run as Server

First run OneInfer as a background server to manage model serving:

nohup oneinfer serve &

This will start a OneInfer server with a web UI in the background for managing model serving. Open your browser and navigate to "http://<your_server_ip>:9090" to access the web UI.

Manage as Client

Start a Model

Start a specific model by specifying its name. You can also define the host and port for the model server.

oneinfer run modelname [-p (default 8080)] [-H (default 127.0.0.1)]

For example:

oneinfer run DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf

This will call the OneInfer server and start the model server.

Status of All Running Models

View the status of all running models:

oneinfer ps

This will list the currently running models along with their status.

Stop a Model

Stop a running model by its unique identifier (UID):

oneinfer stop <model_uid>

Stop the Server

Stop the entire OneInfer server:

oneinfer stop serve

This will stop the server and all running models.

Troubleshooting

  • If you encounter any issues with model downloads, ensure that Python 3 is installed and working properly for the ModelScope and Hugging Face integrations.
  • If a model cannot be started, check if the port is already in use or if any dependency is missing.

For detailed help on each command, use the --help flag:

oneinfer --help

License

OneInfer is open-source software licensed under the MIT license.