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