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:
- 07152a821bbe8e285b7f86b701a43f5078cc840a31ba21f19d985688653945ee
- Size of remote file:
- 268 MB
- SHA256:
- 74238ca1e3a4fa55556ffaaa815722e3b74cd898f8a819be133960b74f28a6f5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.