Instructions to use sravn/e2e-qg-scibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sravn/e2e-qg-scibert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sravn/e2e-qg-scibert") model = AutoModelForSeq2SeqLM.from_pretrained("sravn/e2e-qg-scibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7add255b46aeb7b9975ce8f3706a04634acdb0c03b4c76e2e59c871fd7e295e9
- Size of remote file:
- 993 MB
- SHA256:
- d6822846f33da7617d40c5023eea1ae8567ab328e187cd76a7f89dc6cee5114a
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