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add sparse-finetune toolkit reference to parts 1-4

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thierrypdamiba
2026-03-09 23:31:43 -07:00
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qdrant-landing/content/articles/sparse-embeddings-ecommerce-part-3.md
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We have a trained SPLADE model sitting on a Modal volume (or grab it from [HuggingFace](https://huggingface.co/thierrydamiba/splade-ecommerce-esci)). Now comes the question that matters: is it actually better? In this article, we'll index products into Qdrant, run retrieval benchmarks, implement hard negative mining, and dig into what the model learned. Full evaluation code is in the [GitHub repo](https://github.com/thierrypdamiba/finetune-ecommerce-search).
We have a trained SPLADE model sitting on a Modal volume (or grab it from [HuggingFace](https://huggingface.co/thierrydamiba/splade-ecommerce-esci)). Now comes the question that matters: is it actually better? In this article, we'll index products into Qdrant, run retrieval benchmarks, implement hard negative mining, and dig into what the model learned. Full evaluation code is in the [GitHub repo](https://github.com/thierrypdamiba/finetune-ecommerce-search). To run this entire pipeline on your own data, see the [`sparse-finetune`](https://github.com/qdrant/sparse-finetune) CLI.
## Indexing Products in Qdrant