add a page on local apps

Author: burtenshaw

docs/hub/local-apps.md

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+# Use AI Models Locally
+
+You can run AI models from the Hub locally on your machine. This means that you can benefit from these advantages:
+
+- **Privacy**: You won't be sending your data to a remote server.
+- **Speed**: Your hardware is the limiting factor, not the server or connection speed.
+- **Control**: You can configure models to your liking.
+- **Cost**: You can run models locally without paying for an API provider.
+
+## How to Use Local Apps
+
+Local apps are applications that can run Hugging Face models directly on your machine. To get started:
+
+1. **Enable local apps** in your [Local Apps settings](https://huggingface.co/settings/local-apps).
+
+![Local Apps](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/local-apps/settings.png)
+
+1. **Choose a supported model** from the Hub by searching for it.
+
+![Local Apps](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/local-apps/search_llamacpp.png)
+
+3. **Select the local app** from the "Use this model" dropdown on the model page.
+
+![Local Apps](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/local-apps/button.png)
+
+4. **Copy and run** the provided command in your terminal.
+
+![Local Apps](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/local-apps/command.png)
+
+## Supported Local Apps
+
+The best way to check if a local app is supported is to go to the Local Apps settings and see if the app is listed. Here is a quick overview of some of the most popular local apps:
+
+<Tip>
+
+To use these local apps, copy the snippets from the model card as above.
+
+</Tip>
+
+### Llama.cpp
+
+Llama.cpp is a high-performance C/C++ library for running LLMs locally with optimized inference across different hardware. If you are running a CPU, this is the best option.
+
+**Advantages:**
+- Extremely fast performance for CPU-based models
+- Low resource usage
+- Multiple interface options (CLI, server, Python library)
+- Hardware-optimized for CPU and GPU
+
+To use Llama.cpp, navigate to the model card and click "Use this model" and copy the command.
+
+```sh
+# Load and run the model:
+./llama-server -hf unsloth/gpt-oss-20b-GGUF:Q4_K_M
+```
+
+### LM Studio
+
+LM Studio is a desktop application that provides an easy way to download, run, and experiment with local LLMs.
+
+**Advantages:**
+- Intuitive graphical interface
+- Built-in model browser
+- Developer tools and APIs
+- Free for personal and commercial use
+
+Navigate to the model card and click "Use this model". LM Studio will open and you can start chatting through the interface.
+
+### Jan
+
+Jan is an open-source ChatGPT alternative that runs entirely offline with a user-friendly interface.
+
+**Advantages:**
+- Complete privacy (all data stays local)
+- User-friendly GUI
+- Chat with documents and files
+- OpenAI-compatible API server
+
+To use Jan, navigate to the model card and click "Use this model". Jan will open and you can start chatting through the interface.
+
+### Ollama
+
+Ollama is an application that lets you run large language models locally on your computer with a simple command-line interface.
+
+**Advantages:**
+- Easy installation and setup
+- Direct integration with Hugging Face Hub
+
+To use Ollama, navigate to the model card and click "Use this model" and copy the command.
+
+```sh
+ollama run hf.co/unsloth/gpt-oss-20b-GGUF:Q4_K_M
+```