Details++

README.md

@@ -2,11 +2,15 @@
 tags: autotrain
 language: en
 widget:
-- text: "I quite enjoy using AutoTrain due to its simplicity"
+- text: "I quite enjoy using AutoTrain due to its simplicity."
 datasets:
 - hidude562/autotrain-data-SimpleDetect
 co2_eq_emissions: 0.21691606119445225
 ---
+# Model Description
+This model detects if you are writing in a format that is more similar to Simple English Wikipedia or English Wikipedia. This can be extended to applications that aren't Wikipedia as well.
+
+Please also note there is a major bias to special characters (Mainly the hyphen mark, but it also applies to others) so I would recommend removing them from your input text.
 
 # Model Trained Using AutoTrain
 
@@ -34,7 +38,7 @@ co2_eq_emissions: 0.21691606119445225
 You can use cURL to access this model:
 
 ```
-$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/hidude562/Wiki-Complexity
+$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I quite enjoy using AutoTrain due to its simplicity."}' https://api-inference.huggingface.co/models/hidude562/Wiki-Complexity
 ```
 
 Or Python API:
@@ -46,7 +50,7 @@ model = AutoModelForSequenceClassification.from_pretrained("hidude562/Wiki-Compl
 
 tokenizer = AutoTokenizer.from_pretrained("hidude562/Wiki-Complexity", use_auth_token=True)
 
-inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+inputs = tokenizer("I quite enjoy using AutoTrain due to its simplicity.", return_tensors="pt")
 
 outputs = model(**inputs)
 ```