# 使用 Homebrew 安装 mlx-lm

查看 mlx-lm 的安装路径、可执行文件、元数据以及面向 AI 代理工作流的安全说明。

## 安装

```sh
sudo av install brew:mlx-lm
```

其他安装命令:

### macOS

- Homebrew (100%):

```sh
brew install mlx-lm
```

  证据: local Homebrew formula metadata

## 软件包事实

- **软件包键:** brew:mlx-lm
- **软件包管理器:** Homebrew
- **版本:** 0.31.3
- **来源摘要:** Run LLMs with MLX
- **主页:** <https://github.com/ml-explore/mlx-lm>
- **仓库:** <https://github.com/ml-explore/mlx-lm>
- **最后更新:** 2026-06-20T05:07:43Z
- **已生成:** 2026-08-03T19:37:03+00:00

## 可执行文件

- mlx_lm (别名)
- mlx_lm.awq (别名)
- mlx_lm.benchmark (别名)
- mlx_lm.cache_prompt (别名)
- mlx_lm.chat (别名)
- mlx_lm.convert (别名)
- mlx_lm.dwq (别名)
- mlx_lm.dynamic_quant (别名)
- mlx_lm.evaluate (别名)
- mlx_lm.fuse (别名)
- mlx_lm.generate (别名)
- mlx_lm.gptq (别名)
- mlx_lm.lora (别名)
- mlx_lm.manage (别名)
- mlx_lm.perplexity (别名)
- mlx_lm.server (别名)
- mlx_lm.share (别名)
- mlx_lm.upload (别名)

## 安装行为

- Bottle: 不可用

## 版本和新鲜度

- 页面生成时间: 2026-08-03
- 管理器版本: 0.31.3
## 项目历史与用法

MLX LM is the language-model layer built on top of Apple's MLX array framework. The upstream project describes it as a Python package for generating text and fine-tuning large language models on Apple silicon with MLX. It packages common local-LLM workflows into command-line tools and Python APIs: generation, chat, model conversion, quantization, LoRA and full fine-tuning, benchmarking, prompt caching, upload/share flows, and a local server.

### 项目历史

Its ecosystem role is to make MLX usable for Hugging Face-style LLM work without each user wiring model loading, tokenization, generation loops, quantization, and fine-tuning scripts by hand. The README highlights Hugging Face Hub integration, quantizing and uploading models, low-rank and full fine-tuning with quantized models, and distributed inference and fine-tuning through MLX distributed support. The MLX examples repository points users from earlier LLM examples to MLX LM as the more fully featured package.

### 使用方式

Adoption is tied to the Apple-silicon local-model community. The MLX Community organization on Hugging Face hosts ready-to-use model weights for MLX LM and related MLX projects, and Apple's WWDC material presents MLX LM as the package for running and fine-tuning large language models on Macs. In Homebrew it is a convenience package for users who want the MLX LLM command suite installed as normal CLI tools rather than only through Python packaging.

### 来源

- <https://developer.apple.com/videos/play/wwdc2025/298/>
- <https://formulae.brew.sh/formula/mlx-lm>
- <https://github.com/ml-explore/mlx-examples/blob/main/llms/README.md>
- <https://github.com/ml-explore/mlx-lm>
- <https://huggingface.co/mlx-community>


## 安全说明

broad file, network, media, or database tool signal. formula declares a Homebrew service.

- **Geiger 风险:** orange / 中
- broad file, network, media, or database tool signal
- formula declares a Homebrew service


## Combined YAML source

View the package source record on GitHub. [combined/mlx-lm.yml](https://github.com/mxcl/pkgdb/blob/main/combined/mlx-lm.yml)


## 来源

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- cross-ecosystem install command graph