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mathurvarun84/supply-chain-embeddings

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face

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Supply Chain RAG Embeddings

Fine-tuned all-MiniLM-L6-v2 for supply-chain RAG retrieval (historical precedents, export controls, India sourcing, mitigation QA pairs).

Usage

python

from sentence_transformers import SentenceTransformer
model = SentenceTransformer("mathurvarun84/supply-chain-embeddings")
q = model.encode("Red Sea shipping disruption semiconductor")

Local project

Set in .env:

EMBEDDING_MODEL_PATH=mathurvarun84/supply-chain-embeddings

Then rebuild ChromaDB:

bash

python scripts/build_rag_collections.py --flush