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updated reference to default model
Signed-off-by: Daniele Martinoli <[email protected]>
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docs/rag/ilab-rag-retrieval.md

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@@ -85,10 +85,10 @@ For example, the `vectordb-uri` argument can be implemented using the `click` mo
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The embedding model used to generate text embeddings must be downloaded locally before executing the pipeline.
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For example, this command can be used to download the `sentence-transformers/all-minilm-l6-v2` model to the local models cache:
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For example, this command can be used to download the `ibm-granite/granite-embedding-125m-english` model to the local models cache:
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```bash
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ilab model download -rp sentence-transformers/all-minilm-l6-v2
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ilab model download -rp ibm-granite/granite-embedding-125m-english
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```
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If the configured embedding model has not been cached, the command execution will terminate with an error. This requirement applies
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retriever:
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top_k: 20
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embedder:
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model_name: sentence-transformers/all-minilm-l6-v2
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model_name: ibm-granite/granite-embedding-125m-english
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document_store:
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type: milvuslite
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uri: embeddings.db
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ilab model chat --rag --retriever-type api --retriever-uri http://localhost:8123
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```
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[shareable-excalidraw]: https://excalidraw.com/#json=UNReLpF8DSFoe-zg4w7I8,rZjZB4ZQnpmkM084B4qjkw
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[shareable-excalidraw]: https://excalidraw.com/#json=P2mG25EAjeBRvqzpfIGXv,tlKJPzA2HakGygxJbmn-VQ
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[ilab-knowledge]: https://github.com/instructlab/taxonomy?tab=readme-ov-file#getting-started-with-knowledge-contributions
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[sdg-diff-strategy]: https://github.com/instructlab/sdg/blob/main/src/instructlab/sdg/utils/taxonomy.py
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[chat_template]: https://github.com/instructlab/instructlab/blob/0a773f05f8f57285930df101575241c649f591ce/src/instructlab/configuration.py#L244

docs/rag/images/ingestion-mvp.png

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