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@@ -4,18 +4,11 @@ datasets:
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  - allenai/scirepeval
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  ---
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- ---
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- license: apache-2.0
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- datasets:
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- - allenai/scirepeval
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- language:
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- - en
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- ---
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  **\*\*\*\*\*\*Update\*\*\*\*\*\***
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  This update introduces a new set of SPECTER 2.0 models with the base transformer encoder pre-trained on an extended citation dataset containing more recent papers.
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- For benchmarking purposes please use the existing SPECTER 2.0 models w/o the **aug2023refresh** suffix viz. [allenai/specter2_base](https://huggingface.co/allenai/specter2_base).
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  # SPECTER 2.0 (Base)
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  SPECTER 2.0 is the successor to [SPECTER](https://huggingface.co/allenai/specter) and is capable of generating task specific embeddings for scientific tasks when paired with [adapters](https://huggingface.co/models?search=allenai/specter-2_).
@@ -66,12 +59,12 @@ It builds on the work done in [SciRepEval: A Multi-Format Benchmark for Scientif
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  |Model|Name and HF link|Description|
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  |--|--|--|
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- |Retrieval*|[allenai/specter2_aug2023refresh_proximity](https://huggingface.co/allenai/specter2_aug2023refresh)|Encode papers as queries and candidates eg. Link Prediction, Nearest Neighbor Search|
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- |Adhoc Query|[allenai/specter2_aug2023refresh_adhoc_query](https://huggingface.co/allenai/specter2_aug2023refresh_adhoc_query)|Encode short raw text queries for search tasks. (Candidate papers can be encoded with proximity)|
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  |Classification|[allenai/specter2_aug2023refresh_classification](https://huggingface.co/allenai/specter2_aug2023refresh_classification)|Encode papers to feed into linear classifiers as features|
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  |Regression|[allenai/specter2_aug2023refresh_regression](https://huggingface.co/allenai/specter2_aug2023refresh_regression)|Encode papers to feed into linear regressors as features|
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- *Retrieval model should suffice for downstream task types not mentioned above
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  ```python
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  from transformers import AutoTokenizer, AutoModel
 
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  - allenai/scirepeval
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  ---
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  **\*\*\*\*\*\*Update\*\*\*\*\*\***
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  This update introduces a new set of SPECTER 2.0 models with the base transformer encoder pre-trained on an extended citation dataset containing more recent papers.
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+ For benchmarking purposes please use the existing SPECTER 2.0 [models](https://huggingface.co/allenai/specter2) w/o the **aug2023refresh** suffix.
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  # SPECTER 2.0 (Base)
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  SPECTER 2.0 is the successor to [SPECTER](https://huggingface.co/allenai/specter) and is capable of generating task specific embeddings for scientific tasks when paired with [adapters](https://huggingface.co/models?search=allenai/specter-2_).
 
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  |Model|Name and HF link|Description|
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  |--|--|--|
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+ |Proximity*|[allenai/specter2_aug2023refresh](https://huggingface.co/allenai/specter2_aug2023refresh)|Encode papers as queries and candidates eg. Link Prediction, Nearest Neighbor Search|
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+ |Adhoc Query|[allenai/specter2_aug2023refresh_adhoc_query](https://huggingface.co/allenai/specter2_aug2023refresh_adhoc_query)|Encode short raw text queries for search tasks. (Candidate papers can be encoded with the proximity adapter)|
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  |Classification|[allenai/specter2_aug2023refresh_classification](https://huggingface.co/allenai/specter2_aug2023refresh_classification)|Encode papers to feed into linear classifiers as features|
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  |Regression|[allenai/specter2_aug2023refresh_regression](https://huggingface.co/allenai/specter2_aug2023refresh_regression)|Encode papers to feed into linear regressors as features|
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+ *Proximity model should suffice for downstream task types not mentioned above
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  ```python
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  from transformers import AutoTokenizer, AutoModel