areumtecnologia/bert-text-classification

来源：🤗有风险🏴‍☠️ 救援者：isilicontext-classificationmit109M 参数439 MBsafetensors✓ 7 个校验和877 天前更新

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")

加载中…

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")