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
- Xet hash:
- 6328bec7a34c3e2a7f3508dc934b6a7980caf7dbc8d9bfbfcde9caad5434a7e1
- Size of remote file:
- 54.5 MB
- SHA256:
- fea6ae240aaa6aeb27e73785de3c28c5fb478601c74930336ace019248535ee6
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