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Hugging Face

讓我們載入 Hugging Face Embedding 類別。

%pip install --upgrade --quiet  langchain sentence_transformers
from langchain_huggingface.embeddings import HuggingFaceEmbeddings
embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
text = "This is a test document."
query_result = embeddings.embed_query(text)
query_result[:3]
[-0.04895168915390968, -0.03986193612217903, -0.021562768146395683]
doc_result = embeddings.embed_documents([text])

Hugging Face 推論 API​

我們也可以透過 Hugging Face 推論 API 存取嵌入模型，這不需要我們安裝 sentence_transformers 並在本機下載模型。

import getpass

inference_api_key = getpass.getpass("Enter your HF Inference API Key:\n\n")
Enter your HF Inference API Key:

 ········
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​

我們也可以透過 Hugging Face Hub 套件在本機產生嵌入，這需要我們安裝 huggingface_hub

!pip install huggingface_hub
from langchain_huggingface.embeddings import HuggingFaceEndpointEmbeddings
embeddings = HuggingFaceEndpointEmbeddings()
text = "This is a test document."
query_result = embeddings.embed_query(text)
query_result[:3]

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