# This will return a list of length 1 with the texts and image in a combined embedding

res
```

## Matryoshka Embeddings

Matryoshka learning creates embeddings with coarse-to-fine representation within a single vector; `embed-v4.0` supports multiple output dimensions in the following values: `[256,512,1024,1536]`. To access this, you specify the parameter `output_dimension` when creating the embeddings.

```python PYTHON
texts = ["hello"]

response = co.embed(
    model="embed-v4.0",
    texts=texts,
    output_dimension=1024,
    input_type="classification",
    embedding_types=["float"],
).embeddings