Instructions to use nboudad/Maghribert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nboudad/Maghribert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nboudad/Maghribert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nboudad/Maghribert") model = AutoModelForMaskedLM.from_pretrained("nboudad/Maghribert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nboudad/Maghribert: direct link, hf CLI and curl.
- Browser
- Download file 419 MB
-
https://huggingface.co/nboudad/Maghribert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nboudad/Maghribert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nboudad/Maghribert/resolve/main/pytorch_model.bin
419 MB
- Xet hash:
- 8c022760671f2daae74bf1236a90b970229067c9d30ea7217ad094426c948247
- Size of remote file:
- 419 MB
- SHA256:
- a323f604d5fd809d1f5ec8a2c7c012eca6e37309a39c3125001806d952b50732
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