Update README.md

README.md

@@ -23,7 +23,7 @@ Tested on scoris/en-lt-merged-data validation set. Metric: sacrebleu
 
 | model | testset | BLEU  | Gen Len |
 |----------|---------|-------|-------|
-| scoris/opus-mt-tc-big-lt-en-scoris-finetuned | scoris/en-lt-merged-data (validation) | 43.7767 | 17.8148 
+| scoris/scoris-mt-lt-en | scoris/en-lt-merged-data (validation) | 43.7767 | 17.8148 
 | Helsinki-NLP/opus-mt-tc-big-lt-en | scoris/en-lt-merged-data (validation) | 36.8171 | 17.8284 
 
 According to [Google](https://cloud.google.com/translate/automl/docs/evaluate) BLEU score interpretation is following:
@@ -44,7 +44,7 @@ You can use the model in the following way:
 from transformers import MarianMTModel, MarianTokenizer
 
 # Specify the model identifier on Hugging Face Model Hub
-model_name = "scoris/opus-mt-tc-big-lt-en-scoris-finetuned"
+model_name = "scoris/scoris/scoris-mt-lt-en"
 
 # Load the model and tokenizer from Hugging Face
 tokenizer = MarianTokenizer.from_pretrained(model_name)