Instructions to use Zamachi/t5-for-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zamachi/t5-for-summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Zamachi/t5-for-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("Zamachi/t5-for-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Zamachi/t5-for-summarization: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/Zamachi/t5-for-summarization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Zamachi/t5-for-summarization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Zamachi/t5-for-summarization/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- d96979cd3734821a4319b40c1f1329d9d71428ac29423fd1ebc2326bbae21d6e
- Size of remote file:
- 242 MB
- SHA256:
- de25fa4378cd77b7b5f0958be955b7e5339f53ed9bfdc7c6d0c3e6644cdd4bbc
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