metadata

tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
language: en
license: apache-2.0
datasets:
  - s2orc
  - flax-sentence-embeddings/stackexchange_xml
  - ms_marco
  - gooaq
  - yahoo_answers_topics
  - code_search_net
  - search_qa
  - eli5
  - snli
  - multi_nli
  - wikihow
  - natural_questions
  - trivia_qa
  - embedding-data/sentence-compression
  - embedding-data/flickr30k-captions
  - embedding-data/altlex
  - embedding-data/simple-wiki
  - embedding-data/QQP
  - embedding-data/SPECTER
  - embedding-data/PAQ_pairs
  - embedding-data/WikiAnswers

ONNX version of intfloat/multilingual-e5-large

This is a sentence-transformers model: It maps sentences & paragraphs to a N dimensional dense vector space and can be used for tasks like clustering or semantic search.

The model conversion was made with onnx-convert tool with the following parameters:

python convert.sh --model_id intfloat/multilingual-e5-large --quantize QInt8 --optimize 0

There are two versions of model available:

model.onnx - Float32 version, with optimize=0
model_opt0_QInt8.onnx - QInt8 quantized version, with optimize=0

Compared to the base/small versions of the model, this one is not optimized due to a bug in ONNX runtime: https://github.com/microsoft/onnxruntime/issues/15563

License

Apache 2.0