|
--- |
|
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/e5-base-v2 |
|
|
|
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](https://github.com/nixiesearch/onnx-convert) tool with the following parameters: |
|
|
|
```shell |
|
python convert.sh --model_id intfloat/e5-base-v2 --quantize QInt8 --optimize 2 |
|
``` |
|
|
|
There are two versions of model available: |
|
|
|
* `model.onnx` - Float32 version, with optimize=2 |
|
* `model_opt2_QInt8.onnx` - QInt8 quantized version, with optimize=2 |
|
|
|
## License |
|
|
|
Apache 2.0 |
