diff --git a/bindings/python/src/models.rs b/bindings/python/src/models.rs
index a7fb3a6b..3d4bbda3 100644
--- a/bindings/python/src/models.rs
+++ b/bindings/python/src/models.rs
@@ -5,8 +5,8 @@ use super::utils::Container;
 use pyo3::exceptions;
 use pyo3::prelude::*;
 
-/// Represents any Model to be used with a Tokenizer
-/// This class is to be constructed from specific models
+/// A Model represents some tokenization algorithm like BPE or Word
+/// This class cannot be constructed directly. Please use one of the concrete models.
 #[pyclass]
 pub struct Model {
     pub model: Container<dyn tk::tokenizer::Model + Sync>,
@@ -15,9 +15,9 @@ pub struct Model {
 #[pymethods]
 impl Model {
     #[new]
-    fn new(_obj: &PyRawObject) -> PyResult<Self> {
+    fn new(obj: &PyRawObject) -> PyResult<()> {
         Err(exceptions::Exception::py_err(
-            "Cannot create a Model directly",
+            "Cannot create a Model directly. Use a concrete subclass",
         ))
     }
 }
@@ -29,6 +29,10 @@ pub struct BPE {}
 
 #[pymethods]
 impl BPE {
+    /// from_files(vocab, merges, /)
+    /// --
+    ///
+    /// Instanciate a new BPE model using the provided vocab and merges files
     #[staticmethod]
     fn from_files(vocab: &str, merges: &str) -> PyResult<Model> {
         match tk::models::bpe::BPE::from_files(vocab, merges) {
@@ -44,6 +48,10 @@ impl BPE {
         }
     }
 
+    /// empty()
+    /// --
+    ///
+    /// Instanciate a new BPE model with empty vocab and merges
     #[staticmethod]
     fn empty() -> Model {
         Model {
@@ -51,3 +59,37 @@ impl BPE {
         }
     }
 }
+
+/// WordPiece Model
+#[pyclass]
+pub struct WordPiece {}
+
+#[pymethods]
+impl WordPiece {
+    /// from_files(vocab, /)
+    /// --
+    ///
+    /// Instantiate a new WordPiece model using the provided vocabulary file
+    #[staticmethod]
+    fn from_files(vocab: &str) -> PyResult<Model> {
+        // TODO: Parse kwargs for these
+        let unk_token = String::from("[UNK]");
+        let max_input_chars_per_word = Some(100);
+
+        match tk::models::wordpiece::WordPiece::from_files(
+            vocab,
+            unk_token,
+            max_input_chars_per_word,
+        ) {
+            Err(e) => {
+                println!("Errors: {:?}", e);
+                Err(exceptions::Exception::py_err(
+                    "Error while initializing WordPiece",
+                ))
+            }
+            Ok(wordpiece) => Ok(Model {
+                model: Container::Owned(Box::new(wordpiece)),
+            }),
+        }
+    }
+}