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add sbert example notebook #344

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2 changes: 1 addition & 1 deletion docs/text.rst
Original file line number Diff line number Diff line change
Expand Up @@ -211,7 +211,7 @@ Here we demonstrate the use of `pt.apply.doc_score( , batch_size=128)` to allow
names=["BM25", "BM25 >> BiEncoder", "BM25 >> CrossEncoder"]
)


You can `browse the whole notebook <https://github.com/terrier-org/pyterrier/blob/master/examples/notebooks/sentence_transformers.ipynb>`_ or `try it yourself it on Colab <https://colab.research.google.com/terrier-org/pyterrier/blob/master/examples/notebooks/sentence_transformers.ipynb>`_

References
==========
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1 change: 1 addition & 0 deletions examples/notebooks.md
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Expand Up @@ -28,6 +28,7 @@ This page summarises the available notebooks for PyTerrier.
| Notebook | On Colab? | Description | Read More |
| ---------------- | --------------- | -------------------------------- | ---------- |
| [pt_indexed_epic.ipynb](https://github.com/Georgetown-IR-Lab/OpenNIR/blob/master/examples/pt_indexed_epic.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Georgetown-IR-Lab/OpenNIR/blob/master/examples/pt_indexed_epic.ipynb) | Demonstration of pre-computing EPIC vectors and using them for second-stage scoring using PyTerrier on the TREC COVID benchmark | [OpenNIR repository](https://github.com/Georgetown-IR-Lab/OpenNIR)
| [sentence_transformers.ipynb](https://github.com/terrier-org/pyterrier/blob/master/examples/notebooks/sentence_transformers.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/terrier-org/pyterrier/blob/master/examples/notebooks/sentence_transformers.ipynb) | Demonstration of using pt.apply functions for performing neural reranking with [SentenceTransformers](https://sbert.net/) | [pt.text documentation]([https://github.com/Georgetown-IR-Lab/OpenNIR](https://pyterrier.readthedocs.io/en/latest/text.html#examples-of-sentence-transformers))


## PyTerrier Dense Retrieval
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