Upload README.md with huggingface_hub

README.md

@@ -2,87 +2,24 @@
 tags:
 - vicinity
 - vector-store
-license: mit
-task_categories:
-- summarization
-- translation
-- question-answering
-language:
-- sv
-- da
-- 'no'
-- nn
-- nb
-pretty_name: 'Scandinavian Wikipedai Vector Store '
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: url
-    dtype: string
-  - name: title
-    dtype: string
-  - name: text
-    dtype: string
-  - name: language
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 4019184994
-    num_examples: 3655450
-  download_size: 2020534914
-  dataset_size: 4019184994
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
 ---
 
-# Scandinavian Wikipedia Vector Store
+# Dataset Card for kardosdrur/scandi-wiki-vector-store
 
-This dataset is a lightweight vector store of all Scandinavian Wikipedia articles created with the `static-similarity-mrl-multilingual-v1` embedding model.
-It contains the dataset with metadata, embeddings and a FAISS vector index for approximate nearest neighbour search.
+This dataset was created using the [vicinity](https://github.com/MinishLab/vicinity) library, a lightweight nearest neighbors library with flexible backends.
 
-> This dataset was created using the [vicinity](https://github.com/MinishLab/vicinity) library, a lightweight nearest neighbors library with flexible backends.
-> It contains a vector space with 3655450 items.
+It contains a vector space with 3655450 items.
 
 ## Usage
 
-Install Vicinity with backends, and sentence-transformers:
-
-```bash
-pip install vicinity[all] sentence-transformers
-```
-
-You can load the store using the following code:
+You can load this dataset using the following code:
 
 ```python
 from vicinity import Vicinity
-
-store = Vicinity.load_from_hub("kardosdrur/scandi-wiki-vector-store")
-```
-
-After loading the dataset, you can use the `vicinity.query` method to find the nearest neighbors to a vector:
-
-```python
-from sentence_transformers import SentenceTransformer
-
-encoder = SentenceTransformer("static-similarity-mrl-multilingual-v1")
-query_vector = encoder.encode("Ligger Hinnerup i Aarhus kommune?")
-
-results = store.query(query_vector, k=3)
+vicinity = Vicinity.load_from_hub("kardosdrur/scandi-wiki-vector-store")
 ```
 
-## Reproducing
-
-To reproduce the same dataset, you can use the script supplied in the repo:
-
-```bash
-pip install datasets vicinity[all] sentence-transformers tqdm
-
-python scripts/build_vector_store.py
-```
+After loading the dataset, you can use the `vicinity.query` method to find the nearest neighbors to a vector.
 
 ## Configuration