Update README.md

README.md

@@ -99,7 +99,7 @@ We recommend using the model to respond to human instructions written in natural
 Since this decoder-only model is fine-tuned with wrapper text, we suggest using the same wrapper text to achieve the best performance.
 See the example on the right or the code below.
 
-We now show you how to load and use our model using HuggingFace `pipline()`. 
+We now show you how to load and use our model using HuggingFace `pipeline()`. 
 
 ```python
 # pip install -q transformers
@@ -107,17 +107,19 @@ from transformers import pipeline
 
 checkpoint = "{model_name}" 
 
-model = pipeline('text-generation', model=checkpoint, use_auth_token=True)
+model = pipeline('text-generation', model = checkpoint)
 
 instruction = 'Please let me know your thoughts on the given place and why you think it deserves to be visited: \n"Barcelona, Spain"'
 
 input_prompt = f"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:"
 
-generated_text = generator(input_prompt, max_length=512, do_sample=True)[0]['generated_text']
+generated_text = model(input_prompt, max_length=512, do_sample=True)[0]['generated_text']
 
-print("Response": generated_text)
+print("Response", generated_text)
 ```
 
+
+
 ## Training Procedure
 
 <p align="center" width="100%">