Text Classification
Transformers
Safetensors
distilbert
Sentiment Analysis
Text Classification
BERT
Yelp Reviews
Fine-tuned
text-embeddings-inference
Instructions to use kmack/YELP-Review_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmack/YELP-Review_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kmack/YELP-Review_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kmack/YELP-Review_Classifier") model = AutoModelForSequenceClassification.from_pretrained("kmack/YELP-Review_Classifier") - Notebooks
- Google Colab
- Kaggle
Upload quantized_distilbert.pth with huggingface_hub
Browse files- quantized_distilbert.pth +3 -0
quantized_distilbert.pth
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