Instructions to use activebus/BERT-PT_rest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use activebus/BERT-PT_rest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="activebus/BERT-PT_rest")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("activebus/BERT-PT_rest") model = AutoModelForMaskedLM.from_pretrained("activebus/BERT-PT_rest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1efbe11d0c88f85812725fee961481b1da553f741fd008a5d7394b4fc93c6f0
- Size of remote file:
- 440 MB
- SHA256:
- b5404b0ddfd07babbf46a6a372fd524f90fb9fbf7ac0c339d52cb33e199c8c61
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