Instructions to use nllg/bygpt5-base-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nllg/bygpt5-base-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nllg/bygpt5-base-en")# Load model directly from transformers import AutoModelWithLMHead model = AutoModelWithLMHead.from_pretrained("nllg/bygpt5-base-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fde813addc82506c290a64a1365436ffe59410d329eb3bdd9ffeec1c1f4078b
- Size of remote file:
- 3.38 kB
- SHA256:
- 567a0992a3ba305dc96766572e6853ebcf2a017efb5481409fce52d6433ac7fb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.