Instructions to use activebus/BERT_Review with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use activebus/BERT_Review with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="activebus/BERT_Review")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("activebus/BERT_Review") model = AutoModelForMaskedLM.from_pretrained("activebus/BERT_Review") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8114ca9b33172ba645f41e94ada653e90e78a81e73571dc603cddccd41e9e80c
- Size of remote file:
- 1.34 kB
- SHA256:
- c063bb43c81c928b241a287837e1ef2bbb5bf30212ed4edd4d86c4c11c05dc09
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