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:
- c53eb872d5076f071c3af2f9ca15d8b44a1ae471b62881fefb9148e65bb93da8
- Size of remote file:
- 438 MB
- SHA256:
- c04bd17a824f6416e75fb6928d378355b21f3b01724f94915c554eee867bff69
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