schema_version: 3
id: eidora/text-minilm-l6-v2-light
name: MiniLM_L6_v2_Text
version: 1.0.0
modality: text
license: apache-2.0
bibtex: "@inproceedings{reimers-2019-sentence-bert,\n  title = \"Sentence-BERT: Sentence\
  \ Embeddings using Siamese BERT-Networks\",\n  author = \"Reimers, Nils and Gurevych,\
  \ Iryna\",\n  booktitle = \"Proceedings of EMNLP-IJCNLP\",\n  year = \"2019\",\n\
  \  pages = \"3982--3992\",\n  url = \"https://aclanthology.org/D19-1410/\"\n}"
compatibility:
  min_eidora_version: 0.1.0
artifacts:
- path: model.onnx
  sha256: 14ec04822edb8d74fdf375e0e815acc35a134746f266db2187e5b209a7e45304
  role: graph
- path: tokenizer/special_tokens_map.json
  sha256: 303df45a03609e4ead04bc3dc1536d0ab19b5358db685b6f3da123d05ec200e3
  role: tokenizer
- path: tokenizer/tokenizer.json
  sha256: be50c3628f2bf5bb5e3a7f17b1f74611b2561a3a27eeab05e5aa30f411572037
  role: tokenizer
- path: tokenizer/tokenizer_config.json
  sha256: acb92769e8195aabd29b7b2137a9e6d6e25c476a4f15aa4355c233426c61576b
  role: tokenizer
- path: tokenizer/vocab.txt
  sha256: 07eced375cec144d27c900241f3e339478dec958f92fddbc551f295c992038a3
  role: tokenizer
runtime:
  graph: model.onnx
  inputs:
  - name: input_ids
    source: token_ids
    dtype: int64
    shape:
    - batch
    - 256
  - name: attention_mask
    source: attention_mask
    dtype: int64
    shape:
    - batch
    - 256
  output:
    name: embedding
    dtype: float32
    shape:
    - batch
    - 384
  execution_providers:
  - CUDAExecutionProvider
  - CoreMLExecutionProvider
  - CPUExecutionProvider
preparation:
  tokenizer_path: tokenizer
  max_length: 256
  padding_side: right
  truncation_side: right
  add_special_tokens: true
  prefix: ''
  suffix: ''
  parameters:
    truncation_side:
      default: right
embedding:
  dimensions: 384
  normalized: true
  similarity: cosine
metadata:
  summary: Compact sentence-transformer model producing 384-dimensional embeddings
    for text similarity.
  trained_on: Sentence-pair training data described by the upstream Sentence Transformers
    model card.
  feature_type: embedding
  pooling: attention-mask-aware mean
  group:
    id: text
    label: Text Models
    order: 20
  provenance:
    base_model: sentence-transformers/all-MiniLM-L6-v2
    source_repository: https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
    original_name: all-MiniLM-L6-v2
    original_model_url: https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
    paper_title: 'Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks'
    paper_url: https://aclanthology.org/D19-1410/
    training_data: Sentence-pair training data described by the upstream Sentence
      Transformers model card.
    upstream_license: Apache-2.0
    authors:
    - Sentence Transformers contributors
    source_model: sentence-transformers/all-MiniLM-L6-v2
    source_revision: 1110a243fdf4706b3f48f1d95db1a4f5529b4d41
    exported_opset: 17
    export_date: '2026-10-26'
    exporter_version: eidora-onnx 1.0.0