Transformers
PyTorch
JAX
Safetensors
Russian
English
multilingual
t5
text2text-generation
russian
text-generation-inference
Instructions to use cointegrated/rut5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rut5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-base") model = AutoModelForSeq2SeqLM.from_pretrained("cointegrated/rut5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from cointegrated/rut5-base: direct link, hf CLI and curl.
- Browser
- Download file 977 MB
-
https://huggingface.co/cointegrated/rut5-base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://cointegrated/rut5-base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/cointegrated/rut5-base/resolve/main/flax_model.msgpack
977 MB
- Xet hash:
- 2af6e05b268a764926c71800c4f17c17891dc6b069a61914c815caf60264009f
- Size of remote file:
- 977 MB
- SHA256:
- fd47ded0ca002221fc75317f1f9ebd76b953022ac89972578c9bf890a090223d
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