Instructions to use WeightWatcher/albert-large-v2-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WeightWatcher/albert-large-v2-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="WeightWatcher/albert-large-v2-mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("WeightWatcher/albert-large-v2-mrpc") model = AutoModelForSequenceClassification.from_pretrained("WeightWatcher/albert-large-v2-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Updated model card to reflect new owner
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Added tokenizer configs
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Changed the dataset id
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Added the model and config
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Added a model card
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initial commit
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