Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use cduncanja/emotion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cduncanja/emotion_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cduncanja/emotion_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cduncanja/emotion_model") model = AutoModelForSequenceClassification.from_pretrained("cduncanja/emotion_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bc3b811c44406a2448e33b3e15c1e0c283d0e6248d36594c7d842dc05c8afbd
- Size of remote file:
- 3.38 kB
- SHA256:
- c28a9195111cd01c7168145443dacdc2bebc5bd8440730f2644acb2067e2cdc4
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