Summarization
Transformers
PyTorch
Safetensors
Russian
t5
text2text-generation
russian
text-generation-inference
Instructions to use cointegrated/rut5-base-absum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rut5-base-absum with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="cointegrated/rut5-base-absum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-base-absum") model = AutoModelForSeq2SeqLM.from_pretrained("cointegrated/rut5-base-absum") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0d1686d7b150d344940ee1d3ed74533e6b35db6d202ce3063d178f9be3ec763
- Size of remote file:
- 977 MB
- SHA256:
- 0b520ffeb68a4560543189d01f405454f34e81d5216b1312b823f8ef2f2fec85
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