Update README.md

README.md

@@ -13,20 +13,20 @@ This model is to improve the solving of the code generation problem and implemen
 CoNaLa Dataset for Code Generation is available at
 https://huggingface.co/datasets/AhmedSSoliman/CoNaLa
 
-This is the model is avialable on the huggingface hub https://huggingface.co/AhmedSSoliman/MarianCG-NL-to-Code
+This is the model is avialable on the huggingface hub https://huggingface.co/AhmedSSoliman/MarianCG-CoNaLa
 ```python
 # Model and Tokenizer
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 # model_name = "AhmedSSoliman/MarianCG-NL-to-Code"
-model = AutoModelForSeq2SeqLM.from_pretrained("AhmedSSoliman/MarianCG-NL-to-Code")
-tokenizer = AutoTokenizer.from_pretrained("AhmedSSoliman/MarianCG-NL-to-Code")
+model = AutoModelForSeq2SeqLM.from_pretrained("AhmedSSoliman/MarianCG-CoNaLa")
+tokenizer = AutoTokenizer.from_pretrained("AhmedSSoliman/MarianCG-CoNaLa")
 # Input (Natural Language) and Output (Python Code)
 NL_input = "create array containing the maximum value of respective elements of array `[2, 3, 4]` and array `[1, 5, 2]"
 output = model.generate(**tokenizer(NL_input, padding="max_length", truncation=True, max_length=512, return_tensors="pt"))
 output_code = tokenizer.decode(output[0], skip_special_tokens=True)
 ```
 
-This model is available in spaces using gradio at: https://huggingface.co/spaces/AhmedSSoliman/MarianCG-NL-to-Code
+This model is available in spaces using gradio at: https://huggingface.co/spaces/AhmedSSoliman/MarianCG-CoNaLa
 
 
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