Instructions to use mohammadmahdinouri/relaxed-modernbert-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammadmahdinouri/relaxed-modernbert-checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mohammadmahdinouri/relaxed-modernbert-checkpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("mohammadmahdinouri/relaxed-modernbert-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mohammadmahdinouri/relaxed-modernbert-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 147 MB
-
https://huggingface.co/mohammadmahdinouri/relaxed-modernbert-checkpoints/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mohammadmahdinouri/relaxed-modernbert-checkpoints/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mohammadmahdinouri/relaxed-modernbert-checkpoints/resolve/main/pytorch_model.bin
147 MB
- Xet hash:
- 9a18f33959781fcaa604901a87bf708f86ec5eb68d13573a3e170b507272a42a
- Size of remote file:
- 147 MB
- SHA256:
- 30218b586e1216c1a124dcb6d73bef9d206000083a034acb189f18ca825ad1c4
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