Update README.md

README.md

@@ -30,7 +30,7 @@ It achieves the following results on the evaluation set:
 - Logits/rejected: -0.8732
 - Logits/chosen: -0.9594
 
-# use the model
+# Use the model
 
 ```
 from transformers import AutoTokenizer, AutoModelForCausalLM
@@ -43,18 +43,18 @@ messages = [
     {"role": "user", "content": "Jacques brel, Willem Elsschot en Jan Jambon zitten op café. Waar zouden ze over babbelen?"},
 ]
 
-input_ids = new_tokenizer.apply_chat_template(
+input_ids = tokenizer.apply_chat_template(
     messages,
     add_generation_prompt=True,
     return_tensors="pt"
-).to(new_model.device)
+).to(model.device)
 
 new_terminators = [
-    new_tokenizer.eos_token_id,
-    new_tokenizer.convert_tokens_to_ids("<|eot_id|>")
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
 ]
 
-outputs = new_model.generate(
+outputs = model.generate(
     input_ids,
     max_new_tokens=512,
     eos_token_id=new_terminators,
@@ -63,7 +63,7 @@ outputs = new_model.generate(
     top_p=0.95,
 )
 response = outputs[0][input_ids.shape[-1]:]
-print(new_tokenizer.decode(response, skip_special_tokens=True))
+print(tokenizer.decode(response, skip_special_tokens=True))
 
 ```