Update README.md

README.md

@@ -32,11 +32,11 @@ adapter_name = model.load_adapter("allenai/specter2_aug2023refresh", source="hf"
 
 **\*\*\*\*\*\*Update\*\*\*\*\*\***
 
-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.
-For benchmarking purposes please use the existing SPECTER 2.0 [models](https://huggingface.co/allenai/specter2) w/o the **aug2023refresh** suffix.
+This update introduces a new set of SPECTER2 models with the base transformer encoder pre-trained on an extended citation dataset containing more recent papers.
+For benchmarking purposes please use the existing SPECTER2 [models](https://huggingface.co/allenai/specter2) w/o the **aug2023refresh** suffix.
 
-# SPECTER 2.0 (Base)
-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_).
+# SPECTER2 (Base)
+SPECTER2 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_).
 This is the base model to be used along with the adapters.
 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.
 
@@ -48,7 +48,7 @@ Given the combination of title and abstract of a scientific paper or a short tex
 
 ## Model Description
 
-SPECTER 2.0 has been trained on over 6M triplets of scientific paper citations, which are available [here](https://huggingface.co/datasets/allenai/scirepeval/viewer/cite_prediction_new/evaluation).
+SPECTER2 has been trained on over 6M triplets of scientific paper citations, which are available [here](https://huggingface.co/datasets/allenai/scirepeval/viewer/cite_prediction_new/evaluation).
 Post that it is trained with additionally attached task format specific adapter modules on all the [SciRepEval](https://huggingface.co/datasets/allenai/scirepeval) training tasks.
 
 Task Formats trained on:
@@ -72,9 +72,9 @@ It builds on the work done in [SciRepEval: A Multi-Format Benchmark for Scientif
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [https://github.com/allenai/SPECTER2_0](https://github.com/allenai/SPECTER2_0)
+- **Repository:** [https://github.com/allenai/SPECTER2](https://github.com/allenai/SPECTER2)
 - **Paper:** [https://api.semanticscholar.org/CorpusID:254018137](https://api.semanticscholar.org/CorpusID:254018137)
-- **Demo:** [Usage](https://github.com/allenai/SPECTER2_0/blob/main/README.md)
+- **Demo:** [Usage](https://github.com/allenai/SPECTER2/blob/main/README.md)
 
 # Uses
 
@@ -165,9 +165,9 @@ 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-Adapters](https://huggingface.co/models?search=allenai/specter-2)|**62.3**|**59.2**|**71.2**|**(38.4, 33.0)**|
+|[SPECTER2-Adapters](https://huggingface.co/models?search=allenai/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:
+Please cite the following works if you end up using SPECTER2:
 
 [SPECTER paper](https://api.semanticscholar.org/CorpusID:215768677):