Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use andreaschandra/distilbert-base-uncased-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreaschandra/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="andreaschandra/distilbert-base-uncased-finetuned-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("andreaschandra/distilbert-base-uncased-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("andreaschandra/distilbert-base-uncased-finetuned-emotion") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#4 opened over 1 year ago
by
SFconvertbot
Librarian Bot: Add base_model information to model
#3 opened over 2 years ago
by
librarian-bot
Add evaluation results on the default config and test split of emotion
#2 opened over 3 years ago
by
autoevaluator