Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use yangswei/emotion_text_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangswei/emotion_text_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yangswei/emotion_text_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yangswei/emotion_text_classification") model = AutoModelForSequenceClassification.from_pretrained("yangswei/emotion_text_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cde36e5dd7afd314d37c9a736fef981a75594ede7cca06b5b10c28f1c4737741
- Size of remote file:
- 4.92 kB
- SHA256:
- 0e0c732ff735f3456ab99df1e4d4b1177208029a5eeec162f137cf52e0f86668
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