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")# 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 onnx/model.onnx from answerdotai/ModernBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 596 MB
-
https://huggingface.co/answerdotai/ModernBERT-base/resolve/refs%2Fpr%2F80/onnx/model.onnx
- Command line
-
hf download hf://answerdotai/ModernBERT-base@refs/pr/80/onnx/model.onnx
-
curl -L -o model.onnx https://huggingface.co/answerdotai/ModernBERT-base/resolve/refs%2Fpr%2F80/onnx/model.onnx
596 MB
- Xet hash:
- 64c35a04fb9edb6c1a88dabd7751bbfab5857672dd045a78a6c7c27bb155f3be
- Size of remote file:
- 596 MB
- SHA256:
- 77ee9a4cabca5dee37df42710b34062db7b8ab6b67326e446c6f1dbff798dadb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.