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:
- e66be1dfa80f8ec935a6e78e8471d70f16de00fa09eb86a5536dd1bc170e54a5
- Size of remote file:
- 3.38 kB
- SHA256:
- e82f5cbc75d24facb351edc4c74c40db68aaa0df8d8dc4e986531dcac2ecb380
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