Instructions to use keremp/opus-em-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keremp/opus-em-augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keremp/opus-em-augmented")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("keremp/opus-em-augmented") model = AutoModelForSequenceClassification.from_pretrained("keremp/opus-em-augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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End of training
Kerem Pf3268c2 -
Training in progress, epoch 3
Kerem Pe5ca240 -
Training in progress, epoch 2
Kerem P2b09bb2 -
Training in progress, epoch 1
Kerem P84e775c -
initial commit
Kerem Pee7b1e2