Instructions to use pixelsandpointers/t5-conditioned-next-turn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pixelsandpointers/t5-conditioned-next-turn with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pixelsandpointers/t5-conditioned-next-turn") model = AutoModelForSeq2SeqLM.from_pretrained("pixelsandpointers/t5-conditioned-next-turn") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
53f5a53 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:b01fd1f90f57c494a4ac151d6f9b9ed9c24f6d01ce7c9bb2b433f3d1c1eabb44
size 891727295
|