Instructions to use jbeno/electra-large-classifier-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jbeno/electra-large-classifier-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jbeno/electra-large-classifier-sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, CustomElectraClassifier tokenizer = AutoTokenizer.from_pretrained("jbeno/electra-large-classifier-sentiment") model = CustomElectraClassifier.from_pretrained("jbeno/electra-large-classifier-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Updated README with note about model update and new performance numbers
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Updated to better model from random seed 123 and epoch 10 checkpoint (83.16 vs 82.36 macro F1 on Merged data)
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Added arXiv link, updated citation, edited pip install line
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Changed title to ELECTRA Large
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Initial model files and config for custom ELECTRA Large classifier for sentiment
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initial commit
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