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PCA_model.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:18ff5b016631eb3c04cdd00842865d0c4e135e6ce65e6f143177fbde78c9bff7
-size 6316307
+oid sha256:300a43c7c49be577d802c78b6fcd8b91eaab42065363e0a942abacb74766e5fa
+size 12615443

app_federal.py

@@ -298,7 +298,7 @@ extractive_qa = pipeline("question-answering", model="ai-law-society-lab/extract
 
 ds_paragraphs = load_dataset("ai-law-society-lab/federal-caselaw-paragraphs", token=os.getenv('hf_token'))["train"]
 
-ds = load_dataset("ai-law-society-lab/federal-caselaw-embeddings-PCA", token=os.getenv('hf_token'))["train"]
+ds = load_dataset("ai-law-society-lab/federal-caselaw-embeddings-PCA-768", token=os.getenv('hf_token'))["train"]
 ds = ds.with_format("np")
 faiss_index = load_faiss_index(ds["embeddings"])