In this task, you're given text messages in natural language. Your task is to classify those text messages based on their content into two classes: (1) Spam and (2) Ham messages. If the content of the given message is irrelevant to the receiver or is equally relevant to many other potential recipients then it must be labeled as ‘spam’, otherwise, it should be labeled as ‘ham’.

Example Input: Get 3 Lions England tone, reply lionm 4 mono or lionp 4 poly. 4 more go 2 www.ringtones.co.uk, the original n best. Tones 3GBP network operator rates apply
Example Output: spam

Example Input: HOT LIVE FANTASIES call now 08707509020 Just 20p per min NTT Ltd, PO Box 1327 Croydon CR9 5WB 0870..k
Example Output: spam

Example Input: Wait that's still not all that clear, were you not sure about me being sarcastic or that that's why x doesn't want to live with us
Example Output:
ham