Instructions to use Ulangi/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ulangi/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Ulangi/checkpoints")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Ulangi/checkpoints") model = AutoModelForQuestionAnswering.from_pretrained("Ulangi/checkpoints") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
README.md
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 7e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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