Update README.md

README.md

@@ -12,7 +12,7 @@ pipeline_tag: text-classification
 
 The model expects a sentence and return a number from 1 to 5 where 1 is the most negative sentiment and 5 is the most positive one. There is a parsing present that checks the confidence and if it is below 0.7, it checks for the second most probable result, averages them and uses math.ceil for optimistic behavior.
 
-The model is trained on BERT (nlptown/bert-base-multilingual-uncased-sentiment), which has an MIT license, and distilled llm results (./sentiment.txt)
+The model is trained on BERT (nlptown/bert-base-multilingual-uncased-sentiment), which has an MIT license, and distilled llm results.
 
 Currently the last, and most accurate model is sentiment_model_6_1