# HuggingFaceEndpointEmbeddings

> **Class** in `langchain_huggingface`

📖 [View in docs](https://reference.langchain.com/python/langchain-huggingface/embeddings/huggingface_endpoint/HuggingFaceEndpointEmbeddings)

HuggingFaceHub embedding models.

To use, you should have the `huggingface_hub` python package installed, and the
environment variable `HUGGINGFACEHUB_API_TOKEN` set with your API token, or pass
it as a named parameter to the constructor.

## Signature

```python
HuggingFaceEndpointEmbeddings()
```

## Description

**Example:**

```python
from langchain_huggingface import HuggingFaceEndpointEmbeddings

model = "sentence-transformers/all-mpnet-base-v2"
hf = HuggingFaceEndpointEmbeddings(
    model=model,
    task="feature-extraction",
    huggingfacehub_api_token="my-api-key",
)
```

## Extends

- `BaseModel`
- `Embeddings`

## Properties

- `client`
- `async_client`
- `model`
- `provider`
- `repo_id`
- `task`
- `model_kwargs`
- `huggingfacehub_api_token`
- `model_config`

## Methods

- [`validate_environment()`](https://reference.langchain.com/python/langchain-huggingface/embeddings/huggingface_endpoint/HuggingFaceEndpointEmbeddings/validate_environment)
- [`embed_documents()`](https://reference.langchain.com/python/langchain-huggingface/embeddings/huggingface_endpoint/HuggingFaceEndpointEmbeddings/embed_documents)
- [`aembed_documents()`](https://reference.langchain.com/python/langchain-huggingface/embeddings/huggingface_endpoint/HuggingFaceEndpointEmbeddings/aembed_documents)
- [`embed_query()`](https://reference.langchain.com/python/langchain-huggingface/embeddings/huggingface_endpoint/HuggingFaceEndpointEmbeddings/embed_query)
- [`aembed_query()`](https://reference.langchain.com/python/langchain-huggingface/embeddings/huggingface_endpoint/HuggingFaceEndpointEmbeddings/aembed_query)

---

[View source on GitHub](https://github.com/langchain-ai/langchain/blob/f0c5a28fa05adcda89aebcb449d897245ab21fa4/libs/partners/huggingface/langchain_huggingface/embeddings/huggingface_endpoint.py#L15)