Instructions to use magicslabnu/GERM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magicslabnu/GERM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="magicslabnu/GERM", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("magicslabnu/GERM", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("magicslabnu/GERM", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Add pipeline tag
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by nielsr HF Staff - opened
README.md
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---
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library_name: transformers
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license: mit
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---
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# Model Card for GERM
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2505.00598},
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}
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```
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---
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library_name: transformers
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license: mit
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pipeline_tag: feature-extraction
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---
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# Model Card for GERM
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2505.00598},
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}
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```
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