Instructions to use Billwzl/20split_dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Billwzl/20split_dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Billwzl/20split_dataset")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Billwzl/20split_dataset") model = AutoModelForMaskedLM.from_pretrained("Billwzl/20split_dataset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc428417c7eb0aa0682471ba8b6f4abc074cd01fb193e4813d2105f2a8fd97ad
- Size of remote file:
- 3.31 kB
- SHA256:
- d012f37c597b26e28b18b54d51705aa1ca74a01d99de4f4a5ab6803882a5ae88
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