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Open models & inferencestate-spaces

mamba

An alternative to the transformer: a state space model whose runtime grows linearly with text length. A good fit for long sequences.

Who it is for

For people exploring architectures beyond transformers.

How to start

  1. Install PyTorch first, then: pip install mamba-ssm --no-build-isolation.
  2. Import the block: from mamba_ssm import Mamba.
  3. Run a tensor through Mamba(d_model=16, d_state=16, d_conv=4, expand=2) on a GPU.

Steps are taken from the README. Check the current version in the repository before running them.

Stars over the last 30 days

+103Sep 6 — Oct 6
18,78318,886

Author's description

Mamba SSM architecture

ollama

ollama

The easiest way to run an open model on your own machine: one command downloads and starts it, plus a local REST API and libraries for Python and JavaScript.

182Kstars+2.6K in 30 dGo

huggingface

transformers

The core library for working with models: one codebase for text, vision, audio and multimodal tasks, for both inference and training. Most new open models ship through it.

167Kstars+2.4K in 30 dPython

open-webui

open-webui

A self-hosted ChatGPT-style interface that connects to Ollama and any OpenAI-compatible API. Installs with a single Docker command and runs on your own server.

154Kstars+3.3K in 30 dPython

ggml-org

llama.cpp

A C/C++ engine that runs language models on ordinary hardware: laptops, phones, GPU-less servers. Much of local AI, Ollama included, is built on it.

130Kstars+3.6K in 30 dC++

deepseek-ai

DeepSeek-V3

Repository of the large open DeepSeek-V3 mixture-of-experts model: description, benchmark results and run instructions. It showed an open model can stand next to closed ones.

105Kstars+327 in 30 dPython

pytorch

pytorch

The foundation under most modern neural networks: GPU-accelerated tensors and automatic differentiation, wrapped in ordinary Python. Transformers, Llama and nearly every open model are written on it.

104Kstars+1.1K in 30 dPython