Fill-Mask
Transformers
Safetensors
English
modernbert_small
babylm
babylm-2026
modernbert
masked-language-model
strict-small
custom_code
Instructions to use remg1997/modernbert-small-modernbert-small-factorized-linear-babylm2026 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use remg1997/modernbert-small-modernbert-small-factorized-linear-babylm2026 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="remg1997/modernbert-small-modernbert-small-factorized-linear-babylm2026", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("remg1997/modernbert-small-modernbert-small-factorized-linear-babylm2026", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4933e3eba11d75ea1fab525e687ed8a4b85f592ad9962df93daa9eeccf9ce3dc
- Size of remote file:
- 287 MB
- SHA256:
- c3a00f6495d4933c2e93feb6bc9c81710648d078ed782024960720c95eba37f2
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