# \[Question\] Best practices for using a local embedding model (e.g., Hugging Face) in LangChain?

**URL:** <https://forum.langchain.com/t/question-best-practices-for-using-a-local-embedding-model-e-g-hugging-face-in-langchain/2254>\
**Category:** LangChain Academy\
**Tags:** python-help\
**Created:** [November 19, 2025, 6:20am UTC](https://forum.langchain.com/t/question-best-practices-for-using-a-local-embedding-model-e-g-hugging-face-in-langchain/2254 "2025-11-19T06:20:46Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![Gaodelike](https://yyz1.discourse-cdn.com/flex007/user_avatar/forum.langchain.com/gaodelike/32/1665_2.png) [@Gaodelike](https://forum.langchain.com/u/Gaodelike)\
**Post date:** [November 19, 2025, 6:20am UTC](https://forum.langchain.com/t/question-best-practices-for-using-a-local-embedding-model-e-g-hugging-face-in-langchain/2254/1 "2025-11-19T06:20:46Z")

</div>

Hi everyone,

I am currently working on building a RAG application using LangChain. Due to data privacy/cost constraints, I need to use a **locally hosted embedding model** instead of relying on external APIs like OpenAI.

I have read through the official documentation and searched the forum, but I couldn’t find a clear guide or discussion specifically addressing how to properly configure a local model for this purpose.

**My Goal:** I want to load a model (e.g., **Qwen3-Embedding-0.6B** or a custom local path) to generate embeddings for my documents.

**The Problem:** I am unsure which class is best suited for this or how to point LangChain to my local model weights.

**Current Approach (Pseudocode):**

Python

```auto
# I am trying to achieve something like this:
from langchain_community.embeddings import HuggingFaceEmbeddings

# Is this the correct way to point to a local path?
embeddings = HuggingFaceEmbeddings(
    model_name="/path/to/my/local/model",
    model_kwargs={'device': 'cpu'}
)

```

Could anyone provide a working code snippet or point me to the correct wrapper class for running local embeddings efficiently?

Any help would be greatly appreciated!

Thanks.