Hugging Face
让我们加载 Hugging Face 嵌入类。
python
%pip install --upgrade --quiet langchain sentence_transformerspython
from langchain_huggingface.embeddings import HuggingFaceEmbeddingspython
embeddings = HuggingFaceEmbeddings()python
text = "This is a test document."python
query_result = embeddings.embed_query(text)python
query_result[:3][-0.04895168915390968, -0.03986193612217903, -0.021562768146395683]
python
doc_result = embeddings.embed_documents([text])Hugging Face 推理 API
我们还可以通过 Hugging Face 推理 API 访问嵌入模型，这不需要我们安装 sentence_transformers 并在本地下载模型。
python
import getpass
inference_api_key = getpass.getpass("输入你的 HF 推理 API 密钥:\n\n")text
输入你的 HF 推理 API 密钥:
········python
from langchain_community.embeddings import HuggingFaceInferenceAPIEmbeddings
embeddings = HuggingFaceInferenceAPIEmbeddings(
api_key=inference_api_key, model_name="sentence-transformers/all-MiniLM-l6-v2"
)
query_result = embeddings.embed_query(text)
query_result[:3][-0.038338541984558105, 0.1234646737575531, -0.028642963618040085]
Hugging Face Hub
我们还可以通过 Hugging Face Hub 包在本地生成嵌入，这需要我们安装 huggingface_hub
python
!pip install huggingface_hubpython
from langchain_huggingface.embeddings import HuggingFaceEndpointEmbeddingspython
embeddings = HuggingFaceEndpointEmbeddings()python
text = "This is a test document."python
query_result = embeddings.embed_query(text)python
query_result[:3]