Qdrant FastEmbed Embeddings

LlamaIndex supports FastEmbed for embeddings generation.

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

%pip install llama-index-embeddings-fastembed

%pip install llama-index

To use this provider, the fastembed package needs to be installed.

%pip install fastembed

The list of supported models can be found here.

from llama_index.embeddings.fastembed import FastEmbedEmbedding

embed_model = FastEmbedEmbedding(model_name="BAAI/bge-small-en-v1.5")

100%|██████████| 76.7M/76.7M [00:18<00:00, 4.23MiB/s]

embeddings = embed_model.get_text_embedding("Some text to embed.")
print(len(embeddings))
print(embeddings[:5])

384
[-0.04166769981384277, 0.0018720313673838973, 0.02632238157093525, -0.036030545830726624, -0.014812108129262924]