Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use federicopascual/finetuned-sentiment-analysis-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use federicopascual/finetuned-sentiment-analysis-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="federicopascual/finetuned-sentiment-analysis-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("federicopascual/finetuned-sentiment-analysis-model") model = AutoModelForSequenceClassification.from_pretrained("federicopascual/finetuned-sentiment-analysis-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dde72557f79e3d6de49cbce66d710b999b9b53210a88cb71ac10baa9c86e64d
- Size of remote file:
- 268 MB
- SHA256:
- db4568f8648a3591052fc8093cdc269342aeb04ee0f77aaad77b2e32f246b426
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