Instructions to use cointegrated/rut5-small-style-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rut5-small-style-lm with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-small-style-lm") model = AutoModelForSeq2SeqLM.from_pretrained("cointegrated/rut5-small-style-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from cointegrated/rut5-small-style-lm: direct link, hf CLI and curl.
- Browser
- Download file 259 MB
-
https://huggingface.co/cointegrated/rut5-small-style-lm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://cointegrated/rut5-small-style-lm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cointegrated/rut5-small-style-lm/resolve/main/pytorch_model.bin
259 MB
- Xet hash:
- fde8febfa622735868d68bbff93e6fbbd20c439d79750f589201bb0519751ed5
- Size of remote file:
- 259 MB
- SHA256:
- bbb59c8e42dd7a07e003654edfaf3d9237d4731a46cc75a7bd22d3316ce5213d
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