Update README.md

Typing error:
low_cup_mem_usage instead of low_cpu_mem_usage

Tippfehler bei low_cup_mem_usage

README.md

@@ -33,7 +33,7 @@ The first trick would be to load the model with the specific argument below to l
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
 tokenizer = AutoTokenizer.from_pretrained("Cedille/de-anna")
-model = AutoModelForCausalLM.from_pretrained("Cedille/de-anna", low_cup_mem_usage=True)
+model = AutoModelForCausalLM.from_pretrained("Cedille/de-anna", low_cpu_mem_usage=True)
 ```
 
 We are planning on adding an fp16 branch soon. Combined with the lower memory loading above, loading could be done on 12.1GB of RAM.