Instructions to use LRJ1981/RITO_Version1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LRJ1981/RITO_Version1.0 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LRJ1981/RITO_Version1.0") model = AutoModelForSeq2SeqLM.from_pretrained("LRJ1981/RITO_Version1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LRJ1981/RITO_Version1.0: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/LRJ1981/RITO_Version1.0/resolve/main/training_args.bin
- Command line
-
hf download hf://LRJ1981/RITO_Version1.0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/LRJ1981/RITO_Version1.0/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 3ba3950d670935ae01f4bfe8956821815c2be0f2c124f78239c418a434ede11e
- Size of remote file:
- 5.18 kB
- SHA256:
- e588d45705b34a78a08ec306fd6558ecc34f8b0346279eed034d165506fb2d86
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