Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use jnieus01/bert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jnieus01/bert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jnieus01/bert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jnieus01/bert-emotion") model = AutoModelForSequenceClassification.from_pretrained("jnieus01/bert-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 988d459ec86c69b1475d9c7dfab665ba9334cf2a356686cfbeedc3360075bde6
- Size of remote file:
- 3.39 kB
- SHA256:
- 59bae81ac5a9ac5027e17dfffecfa916bc81bbb389560c3d6e8747c84f810b3a
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