Together AI Embeddings¶

This notebook shows how to use Together AI for embeddings. Together AI provides access to many state-of-the-art embedding models.

Visit https://together.ai and sign up to get an API key.

Setup¶

If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.

In [ ]:

%pip install llama-index-embeddings-together

%pip install llama-index-embeddings-together

In [ ]:

!pip install llama-index

!pip install llama-index

In [ ]:

# You can set the API key in the embeddings or env
# import os
# os.environ["TOEGETHER_API_KEY"] = "your-api-key"

from llama_index.embeddings.together import TogetherEmbedding

embed_model = TogetherEmbedding(
    model_name="togethercomputer/m2-bert-80M-8k-retrieval", api_key="..."
)

# You can set the API key in the embeddings or env # import os # os.environ["TOEGETHER_API_KEY"] = "your-api-key" from llama_index.embeddings.together import TogetherEmbedding embed_model = TogetherEmbedding( model_name="togethercomputer/m2-bert-80M-8k-retrieval", api_key="..." )

Get Embeddings¶

In [ ]:

embeddings = embed_model.get_text_embedding("hello world")

embeddings = embed_model.get_text_embedding("hello world")

In [ ]:

print(len(embeddings))

print(len(embeddings))

768

In [ ]:

print(embeddings[:5])

print(embeddings[:5])

[-0.11657876, -0.012690996, 0.24342081, 0.32781482, 0.022501636]