Instructions to use HUPD/hupd-distilroberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HUPD/hupd-distilroberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HUPD/hupd-distilroberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HUPD/hupd-distilroberta-base") model = AutoModelForMaskedLM.from_pretrained("HUPD/hupd-distilroberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1e8970117de797bd94049b11bbfbf64a820e2b79cedcf95955db0f0c1bafd5b
- Size of remote file:
- 331 MB
- SHA256:
- 495db60bc727912afe2a2c763ce073c9ac2b096bf60705146d28da333f4ff4ef
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.