Update README.md

README.md

@@ -24,8 +24,8 @@ You can use this model by providing a product or brand name as an input. For exa
 ```
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
 
-tokenizer = GPT2Tokenizer.from_pretrained("AdsGPT")
-model = GPT2LMHeadModel.from_pretrained("AdsGPT")
+tokenizer = GPT2Tokenizer.from_pretrained("PeterBrendan/AdsGPT")
+model = GPT2LMHeadModel.from_pretrained("PeterBrendan/AdsGPT")
 
 inputs = tokenizer("Nike Basketball", return_tensors="pt")
 outputs = model.generate(**inputs, max_length=100)
@@ -38,7 +38,7 @@ This model was trained on a dataset consisting of over 10,000 programmatic ad cr
 
 
 **Training procedure:**
-The model was fine-tuned using the GPT-2 base model with the aforementioned training data. The average training loss was 0.16038204793556174.
+The model was fine-tuned using the GPT-2 base model with the aforementioned training data. The training loss was 0.16038204793556174.
 
 
 **Evaluation results:**