Summarization
Transformers
PyTorch
Safetensors
Russian
encoder-decoder
text2text-generation
bert
rubert
Instructions to use dmitry-vorobiev/rubert_ria_headlines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmitry-vorobiev/rubert_ria_headlines 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="dmitry-vorobiev/rubert_ria_headlines")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dmitry-vorobiev/rubert_ria_headlines") model = AutoModelForSeq2SeqLM.from_pretrained("dmitry-vorobiev/rubert_ria_headlines", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85979c3372b22c127f110750678198255680c458ab6bce3f60d99bfcc5863450
- Size of remote file:
- 828 MB
- SHA256:
- 71f249206ee2da240fc75f3b8d228ceee50861ff493ac0b6437e2509ad2754e0
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