Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use umangchaudhry/bert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use umangchaudhry/bert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="umangchaudhry/bert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("umangchaudhry/bert-emotion") model = AutoModelForSequenceClassification.from_pretrained("umangchaudhry/bert-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df22091baa228e35b9f3360511c012eea93d9eb5ea6da3434d09c7fabc9f0081
- Size of remote file:
- 3.18 kB
- SHA256:
- fa3455ebb3bb9c2695318d745a251b55cf91cda4b97c4805930bfb1c3d23238f
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