Instructions to use pachequinho/sentiment_bert_restaurant_10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pachequinho/sentiment_bert_restaurant_10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pachequinho/sentiment_bert_restaurant_10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pachequinho/sentiment_bert_restaurant_10") model = AutoModelForSequenceClassification.from_pretrained("pachequinho/sentiment_bert_restaurant_10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e8cc98546f2a92457726d69a7b28e03f0c647e7d93b8c5927098950b072f70e
- Size of remote file:
- 433 MB
- SHA256:
- 4e6bca51c90200c7de4098b6e32af6f6164b242ab519c5e00104208ae8925806
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