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:
- 26d7d6df889b0d795b077467ef1c48e5f637e594c53fc964da5b8df1ea68c201
- Size of remote file:
- 438 MB
- SHA256:
- ad8ff50d3f5447a09ea7ae03b9e229c30af1da7fc7cb05c69ecd523da20a3695
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