Summarization
Transformers
Safetensors
Russian
t5
text2text-generation
fred-t5
russian
research
rahvusarhiiv
Eval Results (legacy)
text-generation-inference
Instructions to use Rahvusarhiiv/ru_summariser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rahvusarhiiv/ru_summariser 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="Rahvusarhiiv/ru_summariser")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Rahvusarhiiv/ru_summariser") model = AutoModelForSeq2SeqLM.from_pretrained("Rahvusarhiiv/ru_summariser", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token_id": 1, | |
| "decoder_start_token_id": 0, | |
| "early_stopping": true, | |
| "eos_token_id": [ | |
| 2 | |
| ], | |
| "length_penalty": 0.7, | |
| "max_new_tokens": 96, | |
| "min_new_tokens": 0, | |
| "no_repeat_ngram_size": 3, | |
| "num_beams": 4, | |
| "pad_token_id": 0, | |
| "transformers_version": "5.4.0" | |
| } | |