Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use learn2pro/distilbert-base-uncased_emotion_ft_learn2pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use learn2pro/distilbert-base-uncased_emotion_ft_learn2pro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="learn2pro/distilbert-base-uncased_emotion_ft_learn2pro")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("learn2pro/distilbert-base-uncased_emotion_ft_learn2pro") model = AutoModelForSequenceClassification.from_pretrained("learn2pro/distilbert-base-uncased_emotion_ft_learn2pro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files
pytorch_model.bin
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