Create deteccao_sentimentos_em_texto.ipynb

deteccao_sentimentos_em_texto.ipynb

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+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from optimum.intel.openvino import OVModelForSequenceClassification
+
+# Carregar modelo da Hugging Face
+model_name = "distilbert-base-uncased-finetuned-sst-2-english"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Converter para TinyML usando Optimum e OpenVINO
+ov_model = OVModelForSequenceClassification.from_pretrained(model_name, export=True)
+
+# Tokenizar texto de entrada
+text = "I love TinyML!"
+inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+
+# Inferência no modelo otimizado
+outputs = ov_model(**inputs)
+sentiment = "Positive" if outputs.logits.argmax() == 1 else "Negative"
+print("Sentiment:", sentiment)