multilingual e5 large instruct embedding model from intfloat

embedding

735 2 months ago

Readme

Usage

After you pull the image, you can simply use the openai compatible embedding endpoint:

curl -vvvv -H 'Content-Type: application/json' "http://localhost:11434/v1/embeddings" -d '{
  "input": ["passage: my text 1", "passage: my text 2"],
  "model": "jeffh/intfloat-multilingual-e5-large-instruct"
}'

Where model can also include the tag as necessary (such as jeffh/intfloat-multilingual-e5-large-instruct:f16)

Model Notes

You should use the structure for queries:

Instruct: {task_description}
Query: {query}

Documents do not need any special structure to be embedded for indexing.

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