Instructions to use Siki-77/sbert_yelp2class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siki-77/sbert_yelp2class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Siki-77/sbert_yelp2class")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Siki-77/sbert_yelp2class") model = AutoModelForSequenceClassification.from_pretrained("Siki-77/sbert_yelp2class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -10,9 +10,13 @@ Finetune the model "sentence-transformers/all-MiniLM-L6-v2" on Yelp for binary c
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## Model Details
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Epoch Training Loss Validation Loss Accuracy
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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## Model Details
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Epoch Training Loss Validation Loss Accuracy
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1 \ 0.064000 \ 0.061475 \ 0.979474
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2 \ 0.044100 \ 0.070500 \ 0.981158
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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