Tried going from Tswana to Eng as Sub for Sesotho to Eng

app.py

@@ -13,6 +13,8 @@ model = AutoModelForSeq2SeqLM.from_pretrained("souvorinkg/eng-ses-nllb", token=F
 # tokenizer_kin_to_en = AutoTokenizer.from_pretrained("souvorinkg/eng-ses-nllb", token=False, src_lang="kin_Latn", tgt_lang="eng_Latn")
 
 tokenizer_en_to_ses = AutoTokenizer.from_pretrained("souvorinkg/eng-ses-nllb", token=False, src_lang="eng_Latn", tgt_lang="ses_Latn")
+tokenizer_tsn_to_eng = AutoTokenizer.from_pretrained("souvorinkg/eng-ses-nllb", token=False, src_lang="tsn_Latn", tgt_lang="eng_Latn")
+
 
 
 # Define the translation function for English to Kinyarwanda
@@ -30,10 +32,10 @@ tokenizer_en_to_ses = AutoTokenizer.from_pretrained("souvorinkg/eng-ses-nllb", t
 def translate_en_to_ses(SourceText):
     inputs = tokenizer_en_to_ses(SourceText, return_tensors="pt")
     translated_tokens = model.generate(**inputs, max_length=30)
-    return tokenizer_en_to_ses.batch_decode(translated_tokens, skip_special_tokens=True)[0]
+    return tokenizer_tsn_to_eng.batch_decode(translated_tokens, skip_special_tokens=True)[0]
 
 def translate_ses_to_en(SourceText):
-    inputs = inputs = tokenizer_en_to_ses(SourceText, return_tensors="pt")
+    inputs = inputs = tokenizer_tsn_to_eng(SourceText, return_tensors="pt")
     translated_tokens = model.generate(**inputs, max_length=30)
     return tokenizer_en_to_ses.batch_decode(translated_tokens, skip_special_tokens=True)[0]
 
@@ -50,8 +52,8 @@ def translate(SourceText, direction):
     #     return translate_kin_to_en(SourceText)
     if direction == "English to Sesotho":
         return translate_en_to_ses(SourceText)
-    # if direction == "Sesotho to English":
-    #     return translate_ses_to_en(SourceText)
+    if direction == "Sesotho to English":
+        return translate_ses_to_en(SourceText)
     # if direction == "English to Tswana":
     #     return translate == translate_en_to_tsn(SourceText)