Graph Machine Learning
Transformers
Safetensors
graphs_gpt_conditioned
text-generation
biology
medical
chemistry
Instructions to use DaizeDong/GraphsGPT-1W-C with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DaizeDong/GraphsGPT-1W-C with Transformers:
# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("DaizeDong/GraphsGPT-1W-C", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
pipeline_tag: graph-ml
tags:
- biology
- medical
- chemistry
This is the checkpoint of ICML 2024 paper A Graph is Worth K Words: Euclideanizing Graph using Pure Transformer. For more information, please check the GitHub Page.