Instructions to use LRJ1981/Rito_Version1.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LRJ1981/Rito_Version1.2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LRJ1981/Rito_Version1.2") model = AutoModelForSeq2SeqLM.from_pretrained("LRJ1981/Rito_Version1.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 784e2ce397ba96bfa5fdfbd536bbd6f0f254e4bb581a18e4bf107c9e203b86bc
- Size of remote file:
- 595 MB
- SHA256:
- 8374b7ff7e61bbb7eb6a9a777ae4330da14856c6d87d644e5faa027825da32ca
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.