Text Classification
Transformers
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use superlazycoder/autotrain-dating-sentiment-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use superlazycoder/autotrain-dating-sentiment-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="superlazycoder/autotrain-dating-sentiment-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("superlazycoder/autotrain-dating-sentiment-classification") model = AutoModelForSequenceClassification.from_pretrained("superlazycoder/autotrain-dating-sentiment-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4d83bd8c4ac0b3e779eed75c7c900f03f1d70494d0ef69156d9a3a42db1f744
- Size of remote file:
- 4.79 kB
- SHA256:
- 759e38fa0bf62f5c9a7ce0962f06472392c49aff68960e3de7d37c3a3986f0a0
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