Instructions to use unsloth/ModernBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/ModernBERT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="unsloth/ModernBERT-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("unsloth/ModernBERT-base") model = AutoModelForMaskedLM.from_pretrained("unsloth/ModernBERT-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from unsloth/ModernBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 599 MB
-
https://huggingface.co/unsloth/ModernBERT-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://unsloth/ModernBERT-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/unsloth/ModernBERT-base/resolve/main/pytorch_model.bin
599 MB
- Xet hash:
- 9bad9d7ea494c128b5b2a310b7801bc5b3db9fecdac492e4ea2cb290ef1b402d
- Size of remote file:
- 599 MB
- SHA256:
- 9a3b4d34f2367ab3024859dfd744bc898792ec54c577408f78d1f5e44d2cf412
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