Instructions to use answerdotai/ModernBERT-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use answerdotai/ModernBERT-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="answerdotai/ModernBERT-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("answerdotai/ModernBERT-large") model = AutoModelForMaskedLM.from_pretrained("answerdotai/ModernBERT-large") - Notebooks
- Google Colab
- Kaggle
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- [ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) - 22 layers, 149 million parameters
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- [ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) - 28 layers, 395 million parameters
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## Usage
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You can use these models directly with the `transformers` library. Until the next `transformers` release, doing so requires installing transformers from main:
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- [ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) - 22 layers, 149 million parameters
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- [ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) - 28 layers, 395 million parameters
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For more information about ModernBERT, we recommend our [release blog post](https://huggingface.co/blog/modernbert) for a high-level overview, and our [arXiv pre-print](https://arxiv.org/abs/2412.13663) for in-depth information.
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## Usage
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You can use these models directly with the `transformers` library. Until the next `transformers` release, doing so requires installing transformers from main:
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