description update

README.md

@@ -1,8 +1,8 @@
 ---
-title: English Tokipona Translator
-emoji: 📊
+title: English / toki pona Translator
+emoji: 💬
 colorFrom: indigo
-colorTo: blue
+colorTo: purple
 sdk: gradio
 sdk_version: 3.15.0
 app_file: app.py

app.py

@@ -54,10 +54,42 @@ app = gr.Interface(
         ["Its not always perfect, but its pretty okay!", "English", "toki pona", 3],
         ["ilo pi ante toki ni li pona a!", "toki pona", "English", 3],
         ["kijetesantakalu li pona", "toki pona", "English", 3],
+        ["mi li toki e toki pona", "toki pona", "toki pona", 3]
     ],
     cache_examples=False,
-    title="A simple English / toki pona Neural Translation App",
-    description="A simple English / toki pona Neural Translation App"
+    title="English / toki pona Translation",
+    description="""
+    # A simple English / toki pona Neural Machine Translation App!
+    
+    ### toki a! 💬
+
+    This is a simple english to toki pona / toki pona to english neural machine translation app.
+
+    Input your text to translate, a source language and target language, and desired number of return sequences! 
+
+    ### Grammaticality / Regularization
+    English -> English and/or toki pona -> toki pona will result in some form of regularization. 
+    
+    This can approximate grammaticality, but it isn't always the best.
+    
+    For example, "mi li toki e toki pona" [src: toki pona, tgt: toki pona] will result in ['mi toki e toki pona.', 'mi toki pona.', 'mi toki e toki pona']
+    (Thus, the ungrammatical "li" is dropped)
+
+    ### Model and Data
+    This app utilizes a fine-tuned version of Facebook/Meta AI's M2M100 418M param model. 
+    
+    By leveraging the pretrained weights of the massively multilingual M2M100 model, 
+    we can jumpstart our transfer learning to accomplish machine translation for toki pona!
+    
+    The model was fine-tuned on the English/toki pona bitexts found at https://tatoeba.org/
+    
+    ### This app is a work in progress and obviously not all translations will be perfect. 
+    In addition to parameter quantity and the hyper-parameters used while training, 
+    the *quality of data* found on Tatoeba directly influences the perfomance of projects like this! 
+
+    If you wish to contribute, please simply add high quality and diverse translations to Tatoeba!
+
+    """
 )
 
 app.launch()