Instructions to use basic-go/rut5-base-texificator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basic-go/rut5-base-texificator with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("basic-go/rut5-base-texificator") model = AutoModelForSeq2SeqLM.from_pretrained("basic-go/rut5-base-texificator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from basic-go/rut5-base-texificator: direct link, hf CLI and curl.
- Browser
- Download file 828 kB
-
https://huggingface.co/basic-go/rut5-base-texificator/resolve/main/spiece.model
- Command line
-
hf download hf://basic-go/rut5-base-texificator/spiece.model
-
curl -L -o spiece.model https://huggingface.co/basic-go/rut5-base-texificator/resolve/main/spiece.model
828 kB
- Xet hash:
- b5681c7b3af909e77c65d00626f9f17c3c2dca199e29401e213513eb0d3537c8
- Size of remote file:
- 828 kB
- SHA256:
- 76927654c70c667e967c8caca165a3bb1311b415316b6aed8037ed5ede86b10e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.