Instructions to use junzai/bert_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junzai/bert_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="junzai/bert_test")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("junzai/bert_test") model = AutoModelForMaskedLM.from_pretrained("junzai/bert_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7fc7eba1c794f95d9ff87f6281b98058d2d222ed59cb5612c09d825c7b330149
- Size of remote file:
- 438 MB
- SHA256:
- 9032f44cd60e8ccc178a7338fcdc53153550da6fee4f0d7a9e34467e05a78d10
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