Transformers
PyTorch
English
bart
text2text-generation
GENIUS
conditional text generation
sketch-based text generation
keywords-to-text generation
data augmentation
Instructions to use beyond/genius-large-k2t with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beyond/genius-large-k2t with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("beyond/genius-large-k2t") model = AutoModelForSeq2SeqLM.from_pretrained("beyond/genius-large-k2t", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd3f726bf9201535d5270e02510ae74c649af14a9c77aa80c3fd369bbfbce3a2
- Size of remote file:
- 1.63 GB
- SHA256:
- 9980ce72c15ab750d11230c3e9037562d85e59a09b76267dbb15dcc0aefc1ca8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.