diff --git a/bindings/python/examples/example.py b/bindings/python/examples/example.py
index 91f00d3e..e779fd98 100644
--- a/bindings/python/examples/example.py
+++ b/bindings/python/examples/example.py
@@ -61,8 +61,8 @@ elif args.type == "bert":
     print("Running Bert tokenizer")
     tok_p = BertTokenizer.from_pretrained('bert-base-uncased')
 
-    tok_r = Tokenizer(models.WordPiece.from_files(args.vocab))
-    tok_r.with_pre_tokenizer(pre_tokenizers.BasicPreTokenizer.new())
+    tok_r = Tokenizer(models.WordPiece.from_files(args.vocab, unk_token="[UNK]", max_input_chars_per_word=100))
+    tok_r.with_pre_tokenizer(pre_tokenizers.BasicPreTokenizer.new(do_lower_case=True, tokenize_chinese_chars=True, never_split=[]))
     tok_r.with_decoder(decoders.WordPiece.new())
 else:
     raise Exception(f"Unknown type {args.type}")
diff --git a/bindings/python/src/models.rs b/bindings/python/src/models.rs
index 13e7b0e6..cd47931c 100644
--- a/bindings/python/src/models.rs
+++ b/bindings/python/src/models.rs
@@ -4,6 +4,7 @@ use super::utils::Container;
 
 use pyo3::exceptions;
 use pyo3::prelude::*;
+use pyo3::types::*;
 
 /// A Model represents some tokenization algorithm like BPE or Word
 /// This class cannot be constructed directly. Please use one of the concrete models.
@@ -71,10 +72,21 @@ impl WordPiece {
     ///
     /// 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);
+    #[args(kwargs = "**")]
+    fn from_files(vocab: &str, kwargs: Option<&PyDict>) -> PyResult<Model> {
+        let mut unk_token = String::from("[UNK]");
+        let mut max_input_chars_per_word = Some(100);
+
+        if let Some(kwargs) = kwargs {
+            for (key, val) in kwargs {
+                let key: &str = key.extract()?;
+                match key {
+                    "unk_token" => unk_token = val.extract()?,
+                    "max_input_chars_per_word" => max_input_chars_per_word = Some(val.extract()?),
+                    _ => println!("Ignored unknown kwargs option {}", key),
+                }
+            }
+        }
 
         match tk::models::wordpiece::WordPiece::from_files(
             vocab,
diff --git a/bindings/python/src/pre_tokenizers.rs b/bindings/python/src/pre_tokenizers.rs
index 350ba5e6..3a3cd99b 100644
--- a/bindings/python/src/pre_tokenizers.rs
+++ b/bindings/python/src/pre_tokenizers.rs
@@ -43,12 +43,27 @@ pub struct BasicPreTokenizer {}
 #[pymethods]
 impl BasicPreTokenizer {
     #[staticmethod]
-    fn new() -> PyResult<PreTokenizer> {
-        // TODO: Parse kwargs for these
+    #[args(kwargs = "**")]
+    fn new(kwargs: Option<&PyDict>) -> PyResult<PreTokenizer> {
         let mut do_lower_case = true;
         let mut never_split = HashSet::new();
         let mut tokenize_chinese_chars = true;
 
+        if let Some(kwargs) = kwargs {
+            for (key, val) in kwargs {
+                let key: &str = key.extract()?;
+                match key {
+                    "do_lower_case" => do_lower_case = val.extract()?,
+                    "tokenize_chinese_chars" => tokenize_chinese_chars = val.extract()?,
+                    "never_split" => {
+                        let values: Vec<String> = val.extract()?;
+                        never_split = values.into_iter().collect();
+                    }
+                    _ => println!("Ignored unknown kwargs option {}", key),
+                }
+            }
+        }
+
         Ok(PreTokenizer {
             pretok: Container::Owned(Box::new(tk::pre_tokenizers::basic::BasicPreTokenizer::new(
                 do_lower_case,