Instructions to use ayaenna/Bert_reviews with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayaenna/Bert_reviews with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ayaenna/Bert_reviews")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ayaenna/Bert_reviews") model = AutoModelForSequenceClassification.from_pretrained("ayaenna/Bert_reviews") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Bert_reviews
This model is fine-tuned to classify reviews into four categories: Awareness, Consideration, Decision, and Advocacy.
Model Details
This model is based on the bert-base-cased architecture and has been fine-tuned on a dataset of reviews to classify them into one of four categories: Awareness, Consideration, Decision, and Advocacy.
Usage
The model can be used to classify customer reviews into different stages of the customer journey. Simply input a review text, and the model will output the corresponding category.
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