Instructions to use Billwzl/20split_dataset_version3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Billwzl/20split_dataset_version3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Billwzl/20split_dataset_version3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Billwzl/20split_dataset_version3") model = AutoModelForMaskedLM.from_pretrained("Billwzl/20split_dataset_version3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 249487797d58368dbffb1f7ae98b88fb814ed8a7ca6fadb49539a82642687792
- Size of remote file:
- 268 MB
- SHA256:
- 8d1f395702b156a4365f2028f3c080369494db9c77cbf2a859f9da598632ba04
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