60 lines
1.5 KiB
Markdown
60 lines
1.5 KiB
Markdown
---
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pipeline_tag: sentence-similarity
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license: apache-2.0
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tags:
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- sentence-transformers
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- feature-extraction
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- sentence-similarity
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- transformers
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---
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# kornwtp/ConGen-TinyBERT-L6
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This is a [ConGen](https://github.com/KornWtp/ConGen) model: It maps sentences to a 768 dimensional dense vector space and can be used for tasks like semantic search.
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## Usage
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Using this model becomes easy when you have [ConGen](https://github.com/KornWtp/ConGen) installed:
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```
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pip install -U git+https://github.com/KornWtp/ConGen.git
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```
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Then you can use the model like this:
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```python
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from sentence_transformers import SentenceTransformer
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sentences = ["This is an example sentence", "Each sentence is converted"]
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model = SentenceTransformer('kornwtp/ConGen-TinyBERT-L6')
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embeddings = model.encode(sentences)
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print(embeddings)
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```
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## Evaluation Results
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For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [Semantic Textual Similarity](https://github.com/KornWtp/ConGen#main-results---sts)
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## Citing & Authors
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```bibtex
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@inproceedings{limkonchotiwat-etal-2022-congen,
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title = "{ConGen}: Unsupervised Control and Generalization Distillation For Sentence Representation",
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author = "Limkonchotiwat, Peerat and
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Ponwitayarat, Wuttikorn and
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Lowphansirikul, Lalita and
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Udomcharoenchaikit, Can and
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Chuangsuwanich, Ekapol and
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Nutanong, Sarana",
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
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year = "2022",
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publisher = "Association for Computational Linguistics",
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}
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``` |