Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Saiteja/phrasebank-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saiteja/phrasebank-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Saiteja/phrasebank-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Saiteja/phrasebank-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("Saiteja/phrasebank-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 537b7b37477708b14d5c3729714537d10f510016d662bb44d2a3f865aca8ca87
- Size of remote file:
- 4.54 kB
- SHA256:
- 22fb295f162055b91fc1b8bcf66dcb31b52f5ec6c2098bd9fdc4e7fe57bde852
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