Instructions to use nev/dalle-mini-pytorch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nev/dalle-mini-pytorch with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nev/dalle-mini-pytorch") model = AutoModelForSeq2SeqLM.from_pretrained("nev/dalle-mini-pytorch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87491d33ad7d03e7a92a732a155f150c7a8a9a66460bfb64e735488f0006e1e8
- Size of remote file:
- 1.83 GB
- SHA256:
- 654536ef6ed4c4782f82a2d9520a91510ee7cf92cf0cb66ac42bb09d0cb9eda9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.