Instructions to use junzai/bert_finetuning_test1227_hug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junzai/bert_finetuning_test1227_hug with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="junzai/bert_finetuning_test1227_hug")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("junzai/bert_finetuning_test1227_hug") model = AutoModelForMaskedLM.from_pretrained("junzai/bert_finetuning_test1227_hug", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 557e1a440c941a6cbe1dbeaea76509b90de03693c05b0b41d0f01543b19d499e
- Size of remote file:
- 1.22 kB
- SHA256:
- 7dfc52b08edd3b35cd79657220eb70f934b19583a8c4e0ac6b7eaa0ee511f367
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