diff --git a/docs/source/index.rst b/docs/source/index.rst
index 3a30b61b2c..0d5bd01352 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -67,6 +67,7 @@ The library currently contains PyTorch and Tensorflow implementations, pre-train
     main_classes/model
     main_classes/tokenizer
     main_classes/optimizer_schedules
+    main_classes/processors
 
 .. toctree::
     :maxdepth: 2
diff --git a/docs/source/main_classes/processors.rst b/docs/source/main_classes/processors.rst
new file mode 100644
index 0000000000..12e5339ddb
--- /dev/null
+++ b/docs/source/main_classes/processors.rst
@@ -0,0 +1,45 @@
+Processors
+----------------------------------------------------
+
+This library includes processors for several traditional tasks. These processors can be used to process a dataset into
+examples that can be fed to a model.
+
+``GLUE``
+~~~~~~~~~~~~~~~~~~~~~
+
+`General Language Understanding Evaluation (GLUE)<https://gluebenchmark.com/>`__ is a benchmark that evaluates
+the performance of models across a diverse set of existing NLU tasks. It was released together with the paper
+`GLUE: A multi-task benchmark and analysis platform for natural language understanding<https://openreview.net/pdf?id=rJ4km2R5t7>`__
+
+This library hosts a total of 10 processors for the following tasks: MRPC, MNLI, MNLI (mismatched),
+CoLA, SST2, STSB, QQP, QNLI, RTE and WNLI.
+
+.. autoclass:: pytorch_transformers.data.processors.glue.MrpcProcessor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.MnliProcessor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.MnliMismatchedProcessor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.ColaProcessor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.Sst2Processor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.StsbProcessor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.QqpProcessor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.QnliProcessor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.RteProcessor
+    :members:
+
+.. autoclass:: pytorch_transformers.data.processors.glue.WnliProcessor
+    :members: