PORTULAN
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albertina-1b5-portuguese-ptpt-encoder

albertina-100m-portuguese-ptpt

albertina-100m-portuguese-ptbr

albertina-900m-portuguese-ptpt

albertina-900m-portuguese-ptbr

albertina-1b5-portuguese-ptpt

albertina-1b5-portuguese-ptbr

foundation model

Inference Endpoints

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jarodrigues commited on Feb 26, 2024

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Update README.md

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@@ -157,8 +157,8 @@ The model can be used by fine-tuning it for a specific task:
 >>> from transformers import AutoTokenizer, AutoModelForSequenceClassification, TrainingArguments, Trainer
 >>> from datasets import load_dataset
->>> model = AutoModelForSequenceClassification.from_pretrained("PORTULAN/albertina-ptpt-base", num_labels=2)
->>> tokenizer = AutoTokenizer.from_pretrained("PORTULAN/albertina-ptpt-base")
 >>> dataset = load_dataset("PORTULAN/glue-ptpt", "rte")
 >>> def tokenize_function(examples):

 >>> from transformers import AutoTokenizer, AutoModelForSequenceClassification, TrainingArguments, Trainer
 >>> from datasets import load_dataset
+>>> model = AutoModelForSequenceClassification.from_pretrained("PORTULAN/albertina-1b5-portuguese-ptpt-encoder", num_labels=2)
+>>> tokenizer = AutoTokenizer.from_pretrained("PORTULAN/albertina-1b5-portuguese-ptpt-encoder")
 >>> dataset = load_dataset("PORTULAN/glue-ptpt", "rte")
 >>> def tokenize_function(examples):