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----
-license: bsd-3-clause
-configs:
-- config_name: openai-text-embedding-3-large
-  data_files:
-  - split: train
-    path: openai/text-embedding-3-large/*.parquet
-- config_name: snowflake-arctic-embed
-  data_files:
-  - split: train
-    path: ollama/snowflake_arctic/*.parquet
-size_categories:
-- 100K<n<1M
----
-
-##  Loading dataset with vector embeddings
-
-You can load the dataset like this:
-
-```python
-from datasets import load_dataset
-dataset = load_dataset("weaviate/wiki-sample", "openai-text-embedding-3-large", split="train", streaming=True)
-
-for item in dataset:
-    print(item["text"])
-    print(item["title"])
-    print(item["url"])
-    print(item["wiki_id"])
-    print(item["vector"])
-    print()
-```
-
-## Supported Datasets
-* `openai-text-embedding-3-large` - vectors generated with OpenAI using `text-embedding-3-large` model
-* `snowflake-arctic-embed` - vectors generated with Ollama using `snowflake-arctic-embed` model