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Acknowledge ML models used for search. Simplify path used in commands
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README.md
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README.md
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@ -24,7 +24,7 @@ Setup
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python3 processor/org-mode/org-to-jsonl.py \
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--org-files "Schedule.org" "Incoming.org" \
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--org-directory "~/Notes" \
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--jsonl-file ".data/notes.jsonl" \
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--jsonl-file ".notes.jsonl" \
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--compress \
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--verbose
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```
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@ -33,7 +33,7 @@ Run
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---
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Load ML model, generate embeddings and expose API interface to run user queries on above org-mode files
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```sh
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python3 main.py -j .data/notes.jsonl.gz -e .data/notes_embeddings.pt
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python3 main.py -j .notes.jsonl.gz -e .notes_embeddings.pt
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```
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Use
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@ -48,8 +48,8 @@ Use
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- *Call Semantic Search via Python Script Directly*
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```sh
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python3 search_types/asymmetric.py \
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-j .data/notes.jsonl.gz \
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-e .data/notes_embeddings.pt \
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-j .notes.jsonl.gz \
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-e .notes_embeddings.pt \
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-n 5 \
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--verbose \
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--interactive
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@ -57,4 +57,6 @@ Use
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Acknowledgments
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--
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- [MiniLM Model](https://huggingface.co/sentence-transformers/msmarco-MiniLM-L-6-v3) for Asymmetric Text Search. See [SBert Documentation](https://www.sbert.net/examples/applications/retrieve_rerank/README.html)
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- [OpenAI CLIP Model](https://github.com/openai/CLIP) for Image Search. See [SBert Documentation](https://www.sbert.net/examples/applications/image-search/README.html)
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- Charles Cave for [OrgNode Parser](http://members.optusnet.com.au/~charles57/GTD/orgnode.html)
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