aequa-tech
/

sentiment-it

Text Classification

Inference Endpoints

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sfrenda commited on May 30

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@@ -46,7 +46,7 @@ It was tested on SENTIPOLC 2016 test set
 - Accelerate 0.30.0
 # How to use this model:
-```
 model = AutoModelForSequenceClassification.from_pretrained('aequa-tech/sentiment-it',num_labels=3, ignore_mismatched_sizes=True)
 tokenizer = AutoTokenizer.from_pretrained("m-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alb3rt0")
 classifier = pipeline("text-classification", model=model, tokenizer=tokenizer, top_k=None)

 - Accelerate 0.30.0
 # How to use this model:
+```Python
 model = AutoModelForSequenceClassification.from_pretrained('aequa-tech/sentiment-it',num_labels=3, ignore_mismatched_sizes=True)
 tokenizer = AutoTokenizer.from_pretrained("m-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alb3rt0")
 classifier = pipeline("text-classification", model=model, tokenizer=tokenizer, top_k=None)