Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use autoevaluate/multi-class-classification-not-evaluated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/multi-class-classification-not-evaluated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autoevaluate/multi-class-classification-not-evaluated")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/multi-class-classification-not-evaluated") model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/multi-class-classification-not-evaluated") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2 opened about 3 years ago
by
SFconvertbot
Add evaluation results on the default config and test split of emotion
#1 opened over 3 years ago
by
lewtun