Instructions to use Billwzl/20split_dataset_version4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Billwzl/20split_dataset_version4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Billwzl/20split_dataset_version4")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Billwzl/20split_dataset_version4") model = AutoModelForMaskedLM.from_pretrained("Billwzl/20split_dataset_version4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef35ef486f44c1c1c31d3d9a3d9c28586219899d65e303480d897c426d71583c
- Size of remote file:
- 268 MB
- SHA256:
- c0621bb44964512250b26438e8581adbb8b1bd3f3da452031819cc9dcbebce50
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