Instructions to use answerdotai/ModernBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use answerdotai/ModernBERT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="answerdotai/ModernBERT-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("answerdotai/ModernBERT-base") model = AutoModelForMaskedLM.from_pretrained("answerdotai/ModernBERT-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from answerdotai/ModernBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 753 MB
-
https://huggingface.co/answerdotai/ModernBERT-base/resolve/af72838dfd6ee3feb230b60d456e53aac253f9b3/pytorch_model.bin
- Command line
-
hf download hf://answerdotai/ModernBERT-base@af72838dfd6ee3feb230b60d456e53aac253f9b3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/answerdotai/ModernBERT-base/resolve/af72838dfd6ee3feb230b60d456e53aac253f9b3/pytorch_model.bin
753 MB
- Xet hash:
- 0e5399c295db16e6c4a9cd4d38a7ef4da9292ec80fe016fb98d7d7445a31d853
- Size of remote file:
- 753 MB
- SHA256:
- 2a5607cd9b89abf46ecdb8278f785020eddb2ef6b4bd054c37702e699210d2e8
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