Instructions to use Billwzl/20split_dataset_version2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Billwzl/20split_dataset_version2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Billwzl/20split_dataset_version2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Billwzl/20split_dataset_version2") model = AutoModelForMaskedLM.from_pretrained("Billwzl/20split_dataset_version2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 540ef798b42d285485d5ae7032234e3dd9437c5c15c4063c1ebef5142d36f5d3
- Size of remote file:
- 3.38 kB
- SHA256:
- 9fe3968859c886d78dc06794a87d4b7636c4ffa09de6ff529b8a84ee462d1bb9
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