Text Classification
Transformers
PyTorch
Safetensors
Spanish
electra
restaurant
classification
reviews
Instructions to use mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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language: es
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tags:
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- restaurant
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- classification
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- reviews
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widget:
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- text: "No está a la altura, no volveremos."
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---
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# Electricidad-small fine-tuned on restaurant review sentiment analisys dataset
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Test set accuray: 0.86
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