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Create dense vectors using the instructor-large model, running on CPU in quantized mode (fast!)

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InstructorVec

A small vector API service for generating quantized instructor-large vectors. This is used in various other projects under my github repos

Local Installation

pip install -r requirements.txt

or

pip3 install -r requirements.txt

Local Running

uvicorn main:app --host 0.0.0.0 --port 3005

or using python3

python3 -m uvicorn main:app --host 0.0.0.0 --port 3005

Warning: The first run will be VERY slow to load

Visit http://localhost:3005/docs in a browser once it's loaded

Call it in python like this:

# Function to call the text embedder
def embed(text):
    response = requests.get(embedder["embedding_endpoint"], params={"text":text, "instruction": "Represent this text for retrieval:" }, headers={"accept": "application/json"})
    vector_embedding = response.json()
    return vector_embedding

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Create dense vectors using the instructor-large model, running on CPU in quantized mode (fast!)

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