Instructions to use hieule/muprobert-v2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hieule/muprobert-v2.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hieule/muprobert-v2.1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hieule/muprobert-v2.1") model = AutoModelForMaskedLM.from_pretrained("hieule/muprobert-v2.1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 512108c48146f0a10ac0b53b30855307566bec5aa219a6ddc8741b80e39e11c6
- Size of remote file:
- 467 MB
- SHA256:
- dc03af9ea5cad208210c96b7b09d750481ba269f55b77927c1f3539eb9aaa852
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