Instructions to use chtan/ponet-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chtan/ponet-base-uncased with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("chtan/ponet-base-uncased", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## How to Use
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Note: This model requires that trust_remote_code=True be passed to the from_pretrained method. This is because we use a custom model architecture that is not yet part of the transformers package.
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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## How to Use
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Note: This model requires that `trust_remote_code=True` be passed to the from_pretrained method. This is because we use a custom model architecture that is not yet part of the transformers package.
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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