Instructions to use kjunelee/bert-base-uncased-issues-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kjunelee/bert-base-uncased-issues-128 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kjunelee/bert-base-uncased-issues-128")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kjunelee/bert-base-uncased-issues-128") model = AutoModelForMaskedLM.from_pretrained("kjunelee/bert-base-uncased-issues-128", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8168a7cb9b1457ce355ee6376987b0d3c26d6e77afa8807cca26226cb10dfb93
- Size of remote file:
- 3.18 kB
- SHA256:
- 8daa245a3c13acb207277baeb50b62e060a7c449de4f90d81c785f425ec3d485
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