Instructions to use princeton-nlp/bert_base_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use princeton-nlp/bert_base_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="princeton-nlp/bert_base_1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("princeton-nlp/bert_base_1") model = AutoModelForMaskedLM.from_pretrained("princeton-nlp/bert_base_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4289b57f7d6784549a684aa8507e88de55ab593c5ff2d430cdb91ef087ec9584
- Size of remote file:
- 438 MB
- SHA256:
- 3dec35c678bd5ce064de6069be6d32b6aa819b965d8a7737d40b147b9174ff0b
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