Instructions to use MLRS/BERTu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MLRS/BERTu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MLRS/BERTu")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MLRS/BERTu") model = AutoModelForMaskedLM.from_pretrained("MLRS/BERTu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (fc22129efc6c50178663ce35d43c5c781bf8259d) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>0d4fbc3
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