| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - ColBERT |
| - sentence-similarity |
| - feature-extraction |
| - generated_from_trainer |
| - dataset_size:497901 |
| - loss:Contrastive |
| base_model: google/bert_uncased_L-2_H-128_A-2 |
| datasets: |
| - sentence-transformers/msmarco-bm25 |
| pipeline_tag: sentence-similarity |
| --- |
| |
| # Model card for ColBERT v2 BERT Tiny |
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| This is a [ColBERT](https://github.com/stanford-futuredata/ColBERT) model finetuned from [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the [msmarco-bm25](https://huggingface.co/datasets/sentence-transformers/msmarco-bm25) dataset. It maps sentences & paragraphs to sequences of 128-dimensional dense vectors and can be used for semantic textual similarity using the MaxSim operator. |
|
|
| This model is primarily designed for unit tests in limited compute environments such as GitHub Actions. But it does work to an extent for basic use cases. |
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