areumtecnologia/bert-text-classification

Source: 🤗At risk🏴‍☠️ Rescued by: isilicontext-classificationmit109M params439 MBsafetensors✓ 7 checksumsupdated 877d ago

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This model is a test for educational proposits.

To use:


from transformers import pipelineclassifier = pipeline("sentiment-analysis", model="areumtecnologia/bert-text-classification", tokenizer="areumtecnologia/bert-text-classification")
texts = ["I love this movie!", "This is a terrible movie.", "Awesome!", "Very bad!"]
results = classifier(texts)
for text, result in zip(texts, results):
    print(f"Text: {text}\nPrediction: {result}\n")

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This model is a test for educational proposits.

To use:


from transformers import pipelineclassifier = pipeline("sentiment-analysis", model="areumtecnologia/bert-text-classification", tokenizer="areumtecnologia/bert-text-classification")
texts = ["I love this movie!", "This is a terrible movie.", "Awesome!", "Very bad!"]
results = classifier(texts)
for text, result in zip(texts, results):
    print(f"Text: {text}\nPrediction: {result}\n")