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:
- 30f4e0d8a09bb80f8a4aa0de213784e23b733a3541906d48271b0ef8601ea240
- Size of remote file:
- 3.58 kB
- SHA256:
- 040c31756c6faad40f4e81c0b4f9207d37d0e0b446a41096acfedcf1b822b8eb
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