Instructions to use artiquare/initial-bert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use artiquare/initial-bert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="artiquare/initial-bert-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("artiquare/initial-bert-model") model = AutoModelForMaskedLM.from_pretrained("artiquare/initial-bert-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2173b5cca0671956ea3c957a8180ba08985c3049a41d124d030910cc16b7bd67
- Size of remote file:
- 433 MB
- SHA256:
- cf3e28aeed7fe51553bbfa2c42a662415cefcb590030f2a246421ef927c4a720
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