Instructions to use CollectionStudio/ModernBERT-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CollectionStudio/ModernBERT-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CollectionStudio/ModernBERT-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CollectionStudio/ModernBERT-large") model = AutoModelForMaskedLM.from_pretrained("CollectionStudio/ModernBERT-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/model.onnx from CollectionStudio/ModernBERT-large: direct link, hf CLI and curl.
- Browser
- Download file 1.58 GB
-
https://huggingface.co/CollectionStudio/ModernBERT-large/resolve/main/onnx/model.onnx
- Command line
-
hf download hf://CollectionStudio/ModernBERT-large/onnx/model.onnx
-
curl -L -o model.onnx https://huggingface.co/CollectionStudio/ModernBERT-large/resolve/main/onnx/model.onnx
1.58 GB
- Xet hash:
- 06420cf431a6a3f9261cee27f053ffa359f1dbec4a79be3b90f9af22c5038f3a
- Size of remote file:
- 1.58 GB
- SHA256:
- 6bab50009674e7f26bb23023da41c886d1688cba62ea7009521f03a976cff561
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