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")# 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
| { | |
| "decoder_start_token_id": 0, | |
| "eos_token_id": 2, | |
| "length_penalty": 0.6, | |
| "max_length": 256, | |
| "no_repeat_ngram_size": 2, | |
| "num_beams": 10, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.30.2" | |
| } | |