Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use imrazaa/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imrazaa/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="imrazaa/emotion_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("imrazaa/emotion_classification") model = AutoModelForSequenceClassification.from_pretrained("imrazaa/emotion_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27f32832fdb7146758673ab93f2897c44dafd69652bd1f09c17164ff94d73824
- Size of remote file:
- 499 MB
- SHA256:
- 6254bf685e58692106098addf569a473df763b7706aa00a299049dfae35c928f
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