Instructions to use hle2000/graphsormer_subgraphs_reranking_t5large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hle2000/graphsormer_subgraphs_reranking_t5large with Transformers:
# Load model directly from transformers import GraphormerForGraphClassification model = GraphormerForGraphClassification.from_pretrained("hle2000/graphsormer_subgraphs_reranking_t5large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hle2000/graphsormer_subgraphs_reranking_t5large: direct link, hf CLI and curl.
- Browser
- Download file 191 MB
-
https://huggingface.co/hle2000/graphsormer_subgraphs_reranking_t5large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hle2000/graphsormer_subgraphs_reranking_t5large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hle2000/graphsormer_subgraphs_reranking_t5large/resolve/main/pytorch_model.bin
191 MB
- Xet hash:
- c4872e1821347e6ae5cc45f201ed45ea1ae9fa8c0004f596c954d7c4924414e7
- Size of remote file:
- 191 MB
- SHA256:
- dfef3544a74174b63445546c0e63534378bfde94959b43ee99320648a3612637
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