Instructions to use seop/summary_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seop/summary_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("seop/summary_model") model = AutoModelForSeq2SeqLM.from_pretrained("seop/summary_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from seop/summary_model: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/seop/summary_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://seop/summary_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/seop/summary_model/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 299f95d498bde156a5f97267682a34c5400c7cc36a4cc872303730b2db0fee85
- Size of remote file:
- 558 MB
- SHA256:
- 299e74dd58f34e8a13ea69b3ac4c92ebbbce51a66ddb97ddbe421e90a38a24d2
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