forked from Archives/langchain
31 lines
1.2 KiB
Markdown
31 lines
1.2 KiB
Markdown
# Runhouse
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This page covers how to use the [Runhouse](https://github.com/run-house/runhouse) ecosystem within LangChain.
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It is broken into three parts: installation and setup, LLMs, and Embeddings.
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## Installation and Setup
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- Install the Python SDK with `pip install runhouse`
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- If you'd like to use on-demand cluster, check your cloud credentials with `sky check`
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## Self-hosted LLMs
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For a basic self-hosted LLM, you can use the `SelfHostedHuggingFaceLLM` class. For more
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custom LLMs, you can use the `SelfHostedPipeline` parent class.
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```python
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from langchain.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM
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```
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For a more detailed walkthrough of the Self-hosted LLMs, see [this notebook](../modules/models/llms/integrations/self_hosted_examples.ipynb)
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## Self-hosted Embeddings
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There are several ways to use self-hosted embeddings with LangChain via Runhouse.
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For a basic self-hosted embedding from a Hugging Face Transformers model, you can use
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the `SelfHostedEmbedding` class.
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```python
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from langchain.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM
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```
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For a more detailed walkthrough of the Self-hosted Embeddings, see [this notebook](../modules/models/text_embedding/examples/embeddings.ipynb)
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## |