system HF staff commited on
Commit
dc03f7a
1 Parent(s): 4aab736

Update files from the datasets library (from 1.3.0)

Browse files

Release notes: https://github.com/huggingface/datasets/releases/tag/1.3.0

Files changed (1) hide show
  1. README.md +5 -0
README.md CHANGED
@@ -42,6 +42,7 @@ task_ids:
42
  - [Dataset Curators](#dataset-curators)
43
  - [Licensing Information](#licensing-information)
44
  - [Citation Information](#citation-information)
 
45
 
46
  ## Dataset Description
47
 
@@ -159,3 +160,7 @@ English (en)
159
  abstract = "One of the biggest challenges that prohibit the use of many current NLP methods in clinical settings is the availability of public datasets. In this work, we present MeDAL, a large medical text dataset curated for abbreviation disambiguation, designed for natural language understanding pre-training in the medical domain. We pre-trained several models of common architectures on this dataset and empirically showed that such pre-training leads to improved performance and convergence speed when fine-tuning on downstream medical tasks.",
160
  }
161
  ```
 
 
 
 
 
42
  - [Dataset Curators](#dataset-curators)
43
  - [Licensing Information](#licensing-information)
44
  - [Citation Information](#citation-information)
45
+ - [Contributions](#contributions)
46
 
47
  ## Dataset Description
48
 
 
160
  abstract = "One of the biggest challenges that prohibit the use of many current NLP methods in clinical settings is the availability of public datasets. In this work, we present MeDAL, a large medical text dataset curated for abbreviation disambiguation, designed for natural language understanding pre-training in the medical domain. We pre-trained several models of common architectures on this dataset and empirically showed that such pre-training leads to improved performance and convergence speed when fine-tuning on downstream medical tasks.",
161
  }
162
  ```
163
+
164
+ ### Contributions
165
+
166
+ Thanks to [@Narsil](https://github.com/Narsil) for adding this dataset.