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Fake News Agent FAISS Index
FAISS vector store index for the fake news claim verification agent.
Contents
index.faiss— FAISS index (133MB) with 86K embeddings from all-MiniLM-L6-v2index.pkl— Index metadata (16MB)
Usage
from langchain_community.vectorstores import FAISS
from langchain_huggingface import HuggingFaceEmbeddings
emb = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
vs = FAISS.load_local("fakenews_index", emb, allow_dangerous_deserialization=True)
results = vs.similarity_search("your claim", k=5)
Training Data
Built from 86K articles across 6 fake news datasets:
- PolitiFact, GossipCop, WELFake, BuzzFeed, LIAR2, Fake&Real News
License
MIT
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