minicoil tutorial

qdrant-landing/content/documentation/headless/snippets/fastembed/bm25/create-collection/_description.md

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+This code snippet creates a collection configured for BM25-based lexical retrieval. It defines a sparse named vector with the IDF modifier enabled,ensuring that the Inverse Document Frequency, a core component of the BM25 scoring formula, is calculated on Qdrant’s side. This setup allows Qdrant to perform BM25-style retrieval based on keyword frequency and rarity.

qdrant-landing/content/documentation/headless/snippets/fastembed/bm25/create-collection/python.md

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+```python
+client.create_collection(
+    collection_name="{bm25_collection_name}",
+    sparse_vectors_config={
+        "bm25": models.SparseVectorParams(
+            modifier=models.Modifier.IDF
+        )
+    }
+)
+```