Summarization
Transformers
PyTorch
English
t5
text2text-generation
text aggregation
text-generation-inference
Instructions to use toloka/t5-large-for-text-aggregation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toloka/t5-large-for-text-aggregation 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="toloka/t5-large-for-text-aggregation")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("toloka/t5-large-for-text-aggregation") model = AutoModelForSeq2SeqLM.from_pretrained("toloka/t5-large-for-text-aggregation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from toloka/t5-large-for-text-aggregation: direct link, hf CLI and curl.
- Browser
- Download file 2.95 GB
-
https://huggingface.co/toloka/t5-large-for-text-aggregation/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://toloka/t5-large-for-text-aggregation@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/toloka/t5-large-for-text-aggregation/resolve/refs%2Fpr%2F1/pytorch_model.bin
2.95 GB
- Xet hash:
- 6ebe49a9c7198e267d4f0ecf8048c35223235989a5f0e21a5f039f9f91634083
- Size of remote file:
- 2.95 GB
- SHA256:
- e6921adc33a660f3d2c4dc30400460a94aed1e05a5726aeb06eb9ec5785db373
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