Transformers
PyTorch
JAX
Safetensors
Russian
English
t5
text2text-generation
russian
text-generation-inference
Instructions to use cointegrated/rut5-base-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rut5-base-multitask with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-base-multitask") model = AutoModelForSeq2SeqLM.from_pretrained("cointegrated/rut5-base-multitask") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81b9962ce2e1ac5ade07e83172a477b0e89a4550c936450651f9e17cddec0da5
- Size of remote file:
- 977 MB
- SHA256:
- 4d22d421df2b81034fbc2fa35778fd52dde26df11985babd83c76b6d31f4fecf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.