Instructions to use WikiQuality/pre_filtered.ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WikiQuality/pre_filtered.ro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="WikiQuality/pre_filtered.ro")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("WikiQuality/pre_filtered.ro") model = AutoModelForMaskedLM.from_pretrained("WikiQuality/pre_filtered.ro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5295939b21685062282a0eb875cb820c4ce1c72667bd78e5c1d6816e205fb98a
- Size of remote file:
- 1.19 MB
- SHA256:
- cc7259549278552149334825d95b03568b4ee000312dca68815cbe73ef8de0cf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.