Instructions to use jasong2024/bert-finetuned-quick-tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jasong2024/bert-finetuned-quick-tutorial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jasong2024/bert-finetuned-quick-tutorial")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jasong2024/bert-finetuned-quick-tutorial") model = AutoModelForMaskedLM.from_pretrained("jasong2024/bert-finetuned-quick-tutorial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 367acbee723d0f48f8c5170decf9b629734302805c2867870f48fed4689d8d3e
- Size of remote file:
- 438 MB
- SHA256:
- 9af2655bcfcce048fd399bdf9731aec9a41672d436c55453b68b6dc84acad067
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