Instructions to use AT/distilroberta-base-finetuned-wikitext2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AT/distilroberta-base-finetuned-wikitext2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AT/distilroberta-base-finetuned-wikitext2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AT/distilroberta-base-finetuned-wikitext2") model = AutoModelForMaskedLM.from_pretrained("AT/distilroberta-base-finetuned-wikitext2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27c48c933b737158aa83d90401ddf22f6160e13c5791a39c4f781392fc0bfa64
- Size of remote file:
- 329 MB
- SHA256:
- 69816bdb6c80bf598604e4a68de92e12e88341f24c6d99f8f0fcb1711b6a5798
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.