Update README.md

README.md

@@ -6,9 +6,9 @@ datasets:
 - allenai/scirepeval
 ---
 
-# Adapter `allenai/spp_adhoc_query` for allenai/specter_plus_plus
+# Adapter `allenai/specter2_adhoc_query` for allenai/specter2
 
-An [adapter](https://adapterhub.ml) for the `allenai/specter_plus_plus` model that was trained on the [allenai/scirepeval](https://huggingface.co/datasets/allenai/scirepeval/) dataset.
+An [adapter](https://adapterhub.ml) for the `allenai/specter2` model that was trained on the [allenai/scirepeval](https://huggingface.co/datasets/allenai/scirepeval/) dataset.
 
 This adapter was created for usage with the **[adapter-transformers](https://github.com/Adapter-Hub/adapter-transformers)** library.
 
@@ -26,15 +26,15 @@ Now, the adapter can be loaded and activated like this:
 ```python
 from transformers import AutoAdapterModel
 
-model = AutoAdapterModel.from_pretrained("allenai/specter_plus_plus")
-adapter_name = model.load_adapter("allenai/spp_adhoc_query", source="hf", set_active=True)
+model = AutoAdapterModel.from_pretrained("allenai/specter2")
+adapter_name = model.load_adapter("allenai/specter2_adhoc_query", source="hf", set_active=True)
 ```
 
 ## SPECTER 2.0
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-SPECTER 2.0 is the successor to [SPECTER](allenai/specter) and is capable of generating task specific embeddings for scientific tasks when paired with [adapters](https://huggingface.co/models?search=allenai/spp).
+SPECTER 2.0 is the successor to [SPECTER](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).
 Given the combination of title and abstract of a scientific paper or a short texual query, the model can be used to generate effective embeddings to be used in downstream applications.
 
 # Model Details
@@ -50,7 +50,7 @@ Task Formats trained on:
 - Proximity
 - Adhoc Search
 
-This is the adhoc search query specific adapter. For tasks where papers have to retrieved for a short textual query, use this adapter to encode the query and [allenai/spp_proximity](https://huggingface.co/allenai/spp_adhoc_proximity)
+This is the adhoc search query specific adapter. For tasks where papers have to retrieved for a short textual query, use this adapter to encode the query and [allenai/specter2_proximity](https://huggingface.co/allenai/specter2_adhoc_proximity)
 
   
 It builds on the work done in [SciRepEval: A Multi-Format Benchmark for Scientific Document Representations](https://api.semanticscholar.org/CorpusID:254018137) and we evaluate the trained model on this benchmark as well.
@@ -79,23 +79,23 @@ It builds on the work done in [SciRepEval: A Multi-Format Benchmark for Scientif
 
 |Model|Type|Name and HF link|
 |--|--|--|
-|Base|Transformer|[allenai/specter_plus_plus](https://huggingface.co/allenai/specter_plus_plus)|
-|Classification|Adapter|[allenai/spp_classification](https://huggingface.co/allenai/spp_classification)|
-|Regression|Adapter|[allenai/spp_regression](https://huggingface.co/allenai/spp_regression)|
-|Retrieval|Adapter|[allenai/spp_proximity](https://huggingface.co/allenai/spp_proximity)|
-|Adhoc Query|Adapter|[allenai/spp_adhoc_query](https://huggingface.co/allenai/spp_adhoc_query)|
+|Base|Transformer|[allenai/specter2](https://huggingface.co/allenai/specter2)|
+|Classification|Adapter|[allenai/specter2_classification](https://huggingface.co/allenai/specter2_classification)|
+|Regression|Adapter|[allenai/specter2_regression](https://huggingface.co/allenai/specter2_regression)|
+|Retrieval|Adapter|[allenai/specter2_proximity](https://huggingface.co/allenai/specter2_proximity)|
+|Adhoc Query|Adapter|[allenai/specter2_adhoc_query](https://huggingface.co/allenai/specter2_adhoc_query)|
 
 ```python
 from transformers import AutoTokenizer, AutoModel
 
 # load model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained('allenai/specter_plus_plus')
+tokenizer = AutoTokenizer.from_pretrained('allenai/specter2')
 
 #load base model
-model = AutoModel.from_pretrained('allenai/specter_plus_plus')
+model = AutoModel.from_pretrained('allenai/specter2')
 
 #load the adapter(s) as per the required task, provide an identifier for the adapter in load_as argument and activate it
-model.load_adapter("allenai/spp_adhoc_query", source="hf", load_as="spp_adhoc_query", set_active=True)
+model.load_adapter("allenai/specter2_adhoc_query", source="hf", load_as="specter2_adhoc_query", set_active=True)
 
 papers = [{'title': 'BERT', 'abstract': 'We introduce a new language representation model called BERT'},
           {'title': 'Attention is all you need', 'abstract': ' The dominant sequence transduction models are based on complex recurrent or convolutional neural networks'}]
@@ -159,8 +159,8 @@ We also evaluate and establish a new SoTA on [MDCR](https://github.com/zoranmedi
 |[SPECTER](https://huggingface.co/allenai/specter)|54.7|57.4|68.0|(30.6, 25.5)|
 |[SciNCL](https://huggingface.co/malteos/scincl)|55.6|57.8|69.0|(32.6, 27.3)|
 |[SciRepEval-Adapters](https://huggingface.co/models?search=scirepeval)|61.9|59.0|70.9|(35.3, 29.6)|
-|[SPECTER 2.0-base](https://huggingface.co/allenai/specter_plus_plus)|56.3|58.0|69.2|(38.0, 32.4)|
-|[SPECTER 2.0-Adapters](https://huggingface.co/models?search=allen/spp)|**62.3**|**59.2**|**71.2**|**(38.4, 33.0)**|
+|[SPECTER 2.0-base](https://huggingface.co/allenai/specter2)|56.3|58.0|69.2|(38.0, 32.4)|
+|[SPECTER 2.0-Adapters](https://huggingface.co/models?search=allen/specter-2)|**62.3**|**59.2**|**71.2**|**(38.4, 33.0)**|
 
 Please cite the following works if you end up using SPECTER 2.0: