langchain/docs/versioned_docs/version-0.2.x/integrations/providers/runhouse.mdx

# Runhouse

This page covers how to use the [Runhouse](https://github.com/run-house/runhouse) ecosystem within LangChain.
It is broken into three parts: installation and setup, LLMs, and Embeddings.

## Installation and Setup
- Install the Python SDK with `pip install runhouse`
- If you'd like to use on-demand cluster, check your cloud credentials with `sky check`

## Self-hosted LLMs
For a basic self-hosted LLM, you can use the `SelfHostedHuggingFaceLLM` class. For more
custom LLMs, you can use the `SelfHostedPipeline` parent class.

```python
from langchain_community.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM
```

For a more detailed walkthrough of the Self-hosted LLMs, see [this notebook](/docs/integrations/llms/runhouse)

## Self-hosted Embeddings
There are several ways to use self-hosted embeddings with LangChain via Runhouse.

For a basic self-hosted embedding from a Hugging Face Transformers model, you can use 
the `SelfHostedEmbedding` class.
```python
from langchain_community.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM
```

For a more detailed walkthrough of the Self-hosted Embeddings, see [this notebook](/docs/integrations/text_embedding/self-hosted)