Instructions to use GV05/bert-base-uncased-transformers-github-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GV05/bert-base-uncased-transformers-github-128 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GV05/bert-base-uncased-transformers-github-128")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GV05/bert-base-uncased-transformers-github-128") model = AutoModelForMaskedLM.from_pretrained("GV05/bert-base-uncased-transformers-github-128", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29fbadc1a807dc25fb5d89538f3bfc4dc285be44a2861c41ba781665211c95fb
- Size of remote file:
- 3.45 kB
- SHA256:
- d53329887d7fb2a787883cb2f24f6aa6bfaa37501c36250fd3c9944ce4bf3cec
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