Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use berwart/Emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use berwart/Emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="berwart/Emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("berwart/Emotion") model = AutoModelForSequenceClassification.from_pretrained("berwart/Emotion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75a603652d664c3597f24192c1ffcf9ef9b7be1e2165318bc0a8e8917dd67897
- Size of remote file:
- 5.37 kB
- SHA256:
- bb262fc2add97f60680c2b0674e91372eca6298542012b7acd1a58a122dbcfa5
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