Update README.md

README.md

@@ -12,7 +12,7 @@ metrics:
 ![Scoris logo](https://scoris.lt/logo_smaller.png)
 This is an English-Lithuanian translation model based on [Helsinki-NLP/opus-mt-tc-big-en-lt](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-lt)
 
-For Lithuanian-English translation check another model [scoris/opus-mt-tc-big-lt-en-scoris-finetuned](https://huggingface.co/scoris/opus-mt-tc-big-lt-en-scoris-finetuned)
+For Lithuanian-English translation check another model [scoris-mt-lt-en](https://huggingface.co/scoris/scoris-mt-lt-en)
 
 
 Fine-tuned on large merged data set: [scoris/en-lt-merged-data](https://huggingface.co/datasets/scoris/en-lt-merged-data) (5.4 million sentence pairs)
@@ -26,7 +26,7 @@ Tested on scoris/en-lt-merged-data validation set. Metric: sacrebleu
 
 | model | testset | BLEU  | Gen Len |
 |----------|---------|-------|-------|
-| scoris/opus-mt-tc-big-en-lt-scoris-finetuned | scoris/en-lt-merged-data (validation) | 41.8841 	 | 17.4785
+| scoris/scoris-mt-en-lt | scoris/en-lt-merged-data (validation) | 41.8841 	 | 17.4785
 | Helsinki-NLP/opus-mt-tc-big-en-lt | scoris/en-lt-merged-data (validation) | 34.2768 | 17.6664
 
 According to [Google](https://cloud.google.com/translate/automl/docs/evaluate) BLEU score interpretation is following:
@@ -47,7 +47,7 @@ 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-en-lt-scoris-finetuned"
+model_name = "scoris/scoris-mt-en-lt
 
 # Load the model and tokenizer from Hugging Face
 tokenizer = MarianTokenizer.from_pretrained(model_name)