Instructions to use Kaspar/modernbert_pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kaspar/modernbert_pretrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Kaspar/modernbert_pretrained")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Kaspar/modernbert_pretrained") model = AutoModelForMaskedLM.from_pretrained("Kaspar/modernbert_pretrained") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
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This model is a fine-tuned version of [Kaspar/ecco_modernbert_pretrained](https://huggingface.co/Kaspar/ecco_modernbert_pretrained) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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## Model description
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This model is a fine-tuned version of [Kaspar/ecco_modernbert_pretrained](https://huggingface.co/Kaspar/ecco_modernbert_pretrained) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1759
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## Model description
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