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_quantized.onnx from CollectionStudio/ModernBERT-large: direct link, hf CLI and curl.
- Browser
- Download file 398 MB
-
https://huggingface.co/CollectionStudio/ModernBERT-large/resolve/main/onnx/model_quantized.onnx
- Command line
-
hf download hf://CollectionStudio/ModernBERT-large/onnx/model_quantized.onnx
-
curl -L -o model_quantized.onnx https://huggingface.co/CollectionStudio/ModernBERT-large/resolve/main/onnx/model_quantized.onnx
398 MB
- Xet hash:
- c47aeb0be26a8846ac56cf0c495cc212cd3c2a1d4e435c46d2406ccc267a7ce9
- Size of remote file:
- 398 MB
- SHA256:
- 84baefd65face547d9090dfa591ba15eae35eaaa84a2eae5e75b9fd47f6ebe85
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