Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Etelis/YELP_BERT_5E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Etelis/YELP_BERT_5E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Etelis/YELP_BERT_5E")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Etelis/YELP_BERT_5E") model = AutoModelForSequenceClassification.from_pretrained("Etelis/YELP_BERT_5E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ae8eb8d8b8b63673d2a5428d6aa1507b52073f25a48971d17e7b87b223cb57e
- Size of remote file:
- 433 MB
- SHA256:
- ba9c1a38780f1ddc2c0bbea0f7b4df8e7b597962249aa8e573da05a34d80f211
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