Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use bergum/xtremedistil-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bergum/xtremedistil-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bergum/xtremedistil-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bergum/xtremedistil-emotion") model = AutoModelForSequenceClassification.from_pretrained("bergum/xtremedistil-emotion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a9a708d3ff32031c92647bedf14a3f83cd9e312020dfe66711d56452dbb5d9a
- Size of remote file:
- 51.1 MB
- SHA256:
- cb57404d5ab2492e10541f373b025e5ac97d5e563838bf06796c3a764049b1c1
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