Summarization
Transformers
PyTorch
Safetensors
Russian
English
t5
text2text-generation
dialogue-summarization
Eval Results (legacy)
text-generation-inference
Instructions to use d0rj/rut5-base-summ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use d0rj/rut5-base-summ 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="d0rj/rut5-base-summ")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("d0rj/rut5-base-summ") model = AutoModelForSeq2SeqLM.from_pretrained("d0rj/rut5-base-summ", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from d0rj/rut5-base-summ: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/d0rj/rut5-base-summ/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://d0rj/rut5-base-summ/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/d0rj/rut5-base-summ/resolve/main/pytorch_model.bin
892 MB
- Xet hash:
- 3182bcef00b07f81671c5d16e86673af97f2b5dcbd0f7756f1ccf9785f4a1b10
- Size of remote file:
- 892 MB
- SHA256:
- bafa4d4fad625ac774b6d86c9a2da33715e797e926ccc6b95e660fc08da9e8f1
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