diff --git a/src/lib.rs b/src/lib.rs
index e3978000..695c529e 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -10,18 +10,28 @@ mod python_bindings;
 
 use thiserror::Error;
 
-#[derive(Error, Debug)]
+#[derive(Error, Debug, PartialEq)]
 pub enum Error {
     #[error("The vocabulary does not allow us to build a sequence that matches the input")]
     IndexError,
 }
 
 #[derive(Error, Debug)]
+#[error("Tokenizer error")]
+pub struct TokenizerError(tokenizers::Error);
+
+impl PartialEq for TokenizerError {
+    fn eq(&self, other: &Self) -> bool {
+        self.0.to_string() == other.0.to_string()
+    }
+}
+
+#[derive(Error, Debug, PartialEq)]
 pub enum VocabularyError {
     #[error("Unable to create tokenizer for {model}, source {source}")]
     UnableToCreateTokenizer {
         model: String,
-        source: tokenizers::Error,
+        source: TokenizerError,
     },
     #[error("Unable to locate EOS token for {model}")]
     UnableToLocateEosTokenId { model: String },
@@ -29,7 +39,7 @@ pub enum VocabularyError {
     TokenProcessorError(#[from] TokenProcessorError),
 }
 
-#[derive(Error, Debug)]
+#[derive(Error, Debug, PartialEq)]
 pub enum TokenProcessorError {
     #[error("Tokenizer is not supported")]
     UnsupportedTokenizer,
diff --git a/src/vocabulary/mod.rs b/src/vocabulary/mod.rs
index 2851752d..fef311f4 100644
--- a/src/vocabulary/mod.rs
+++ b/src/vocabulary/mod.rs
@@ -3,8 +3,7 @@ use std::collections::HashMap;
 use tokenizers::normalizers::Sequence;
 use tokenizers::{FromPretrainedParameters, NormalizerWrapper, Tokenizer};
 
-use crate::prelude::*;
-use crate::VocabularyError;
+use crate::{prelude::*, TokenizerError, VocabularyError};
 
 use locator::EosTokenLocator;
 use processor::TokenProcessor;
@@ -50,7 +49,7 @@ impl Vocabulary {
             Tokenizer::from_pretrained(model, parameters.clone()).map_err(|error| {
                 VocabularyError::UnableToCreateTokenizer {
                     model: model.to_string(),
-                    source: error,
+                    source: TokenizerError(error),
                 }
             })?;
         Self::filter_normalizers(&mut tokenizer);
@@ -305,4 +304,64 @@ mod tests {
             }
         }
     }
+
+    #[test]
+    fn token_processor_error() {
+        let model = "hf-internal-testing/tiny-random-XLMRobertaXLForCausalLM";
+        let vocabulary = Vocabulary::from_pretrained(model, None);
+
+        assert!(vocabulary.is_err());
+        if let Err(e) = vocabulary {
+            assert_eq!(
+                e,
+                VocabularyError::TokenProcessorError(
+                    crate::TokenProcessorError::UnsupportedTokenizer
+                )
+            )
+        }
+    }
+
+    #[test]
+    fn tokenizer_error() {
+        let model = "hf-internal-testing/some-non-existent-model";
+        let vocabulary = Vocabulary::from_pretrained(model, None);
+
+        assert!(vocabulary.is_err());
+        if let Err(VocabularyError::UnableToCreateTokenizer { model, source }) = vocabulary {
+            assert_eq!(model, model.to_string());
+            assert_eq!(source.to_string(), "Tokenizer error".to_string());
+        }
+    }
+
+    #[test]
+    fn prepend_normalizers_filtered_out() {
+        use tokenizers::normalizers::{Prepend, Sequence};
+
+        let prepend = Prepend::new("_".to_string());
+        let prepend_normalizer = NormalizerWrapper::Prepend(prepend);
+        let sequence = Sequence::new(vec![prepend_normalizer.clone()]);
+        let sequence_normalizer = NormalizerWrapper::Sequence(sequence);
+
+        let model = "hf-internal-testing/llama-tokenizer";
+        let tokenizer = Tokenizer::from_pretrained(model, None).expect("Tokenizer failed");
+
+        for normalizer in [prepend_normalizer, sequence_normalizer] {
+            let mut normalized_t = tokenizer.clone();
+            normalized_t.with_normalizer(Some(normalizer));
+            Vocabulary::filter_normalizers(&mut normalized_t);
+            if let Some(n) = normalized_t.get_normalizer() {
+                match n {
+                    NormalizerWrapper::Sequence(seq) => {
+                        for n in seq.get_normalizers() {
+                            if let NormalizerWrapper::Prepend(_) = n {
+                                unreachable!()
+                            }
+                        }
+                    }
+                    NormalizerWrapper::Prepend(_) => unreachable!(),
+                    _ => {}
+                }
+            }
+        }
+    }
 }
diff --git a/src/vocabulary/processor.rs b/src/vocabulary/processor.rs
index 5048b11e..ce149f80 100644
--- a/src/vocabulary/processor.rs
+++ b/src/vocabulary/processor.rs
@@ -194,7 +194,7 @@ impl TokenProcessor {
         }
     }
 
-    /// Process each token based on the level ofTokenProcesso.
+    /// Process each token based on the level of `TokenProcessor`.
     pub(crate) fn process(&self, token: String) -> Result<Vec<u8>> {
         match &self.level {
             TokenProcessorLevel::Byte => {
@@ -312,4 +312,44 @@ mod tests {
             assert_eq!(processed, expected);
         }
     }
+
+    #[test]
+    fn unsupported_tokenizer_error() {
+        let model = "hf-internal-testing/tiny-random-XLMRobertaXLForCausalLM";
+        let tokenizer = Tokenizer::from_pretrained(model, None).expect("Tokenizer failed");
+
+        let result = TokenProcessor::new(&tokenizer);
+        assert!(result.is_err());
+        if let Err(e) = result {
+            assert_eq!(e, TokenProcessorError::UnsupportedTokenizer)
+        }
+    }
+
+    #[test]
+    fn byte_processor_error() {
+        let model = "openai-community/gpt2";
+        let tokenizer = Tokenizer::from_pretrained(model, None).expect("Tokenizer failed");
+        let processor = TokenProcessor::new(&tokenizer).expect("Processor failed");
+
+        for token in ["𝒜𝒷𝒸𝒟𝓔", "🦄🌈🌍🔥🎉", "京东购物"] {
+            let result = processor.process(token.to_string());
+            assert!(result.is_err());
+            if let Err(e) = result {
+                assert_eq!(e, TokenProcessorError::ByteProcessorFailed)
+            }
+        }
+    }
+
+    #[test]
+    fn byte_fallback_processor_error() {
+        let model = "hf-internal-testing/llama-tokenizer";
+        let tokenizer = Tokenizer::from_pretrained(model, None).expect("Tokenizer failed");
+        let processor = TokenProcessor::new(&tokenizer).expect("Processor failed");
+
+        let result = processor.process("<0x6y>".to_string());
+        assert!(result.is_err());
+        if let Err(e) = result {
+            assert_eq!(e, TokenProcessorError::ByteFallbackProcessorFailed)
+        }
+    }
 }