Instructions to use LRJ1981/Rito_version1.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LRJ1981/Rito_version1.3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LRJ1981/Rito_version1.3") model = AutoModelForSeq2SeqLM.from_pretrained("LRJ1981/Rito_version1.3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LRJ1981/Rito_version1.3: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/LRJ1981/Rito_version1.3/resolve/main/training_args.bin
- Command line
-
hf download hf://LRJ1981/Rito_version1.3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/LRJ1981/Rito_version1.3/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 2a212a55b6e0ed77177018d1e1a3ad256fd43a26520deb2bb140fc582552645b
- Size of remote file:
- 5.3 kB
- SHA256:
- d6913eb9d58794495bdb8fa42b42e63d84fe2ea54099ac18792d8c55c96ef3bd
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