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---
language:
- en
license: bsd-3-clause
size_categories:
- 100K<n<1M
configs:
- config_name: no-vectors
data_files: no-vectors/*.parquet
default: true
- config_name: openai-text-embedding-3-small
data_files: openai/text-embedding-3-small/*.parquet
- config_name: openai-text-embedding-3-large
data_files: openai/text-embedding-3-large/*.parquet
- config_name: snowflake-arctic-embed
data_files: ollama/snowflake-arctic/*.parquet
---
## Loading dataset without vector embeddings
You can load the raw dataset without vectors, like this:
```python
from datasets import load_dataset
dataset = load_dataset("weaviate/wiki-sample", split="train", streaming=True)
```
## Loading dataset with vector embeddings
You can also load the dataset with vectors, like this:
```python
from datasets import load_dataset
dataset = load_dataset("weaviate/wiki-sample", "openai-text-embedding-3-small", split="train", streaming=True)
# dataset = load_dataset("weaviate/wiki-sample", "snowflake-arctic-embed", 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
### Data only - no vectors
```python
from datasets import load_dataset
dataset = load_dataset("weaviate/wiki-sample", "no-vectors", split="train", streaming=True)
```
You can also skip the config name, as "no-vectors is the default dataset:
```python
from datasets import load_dataset
dataset = load_dataset("weaviate/wiki-sample", split="train", streaming=True)
```
### OpenAI
**text-embedding-3-small** - 1536d vectors - generated with OpenAI
```python
from datasets import load_dataset
dataset = load_dataset("weaviate/wiki-sample", "openai-text-embedding-3-small", split="train", streaming=True)
```
**text-embedding-3-large** - 3072d vectors - generated with OpenAI
```python
from datasets import load_dataset
dataset = load_dataset("weaviate/wiki-sample", "openai-text-embedding-3-large", split="train", streaming=True)
```
### Snowflake
**snowflake-arctic-embed** - 1024 vectors - generated with Ollama
```python
from datasets import load_dataset
dataset = load_dataset("weaviate/wiki-sample", "snowflake-arctic-embed", split="train", streaming=True)
```
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