Instructions to use marksverdhei/flan-t5-large-multiqg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marksverdhei/flan-t5-large-multiqg with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("marksverdhei/flan-t5-large-multiqg") model = AutoModelForSeq2SeqLM.from_pretrained("marksverdhei/flan-t5-large-multiqg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c51699edc1d7791d2d514bd8272653b0a27045c4178e7f3a911c19a015e4ddc
- Size of remote file:
- 3.13 GB
- SHA256:
- 46cb94d6b522ac9f907617eb8e91b9161c71df136ac8f8ea3e98c67f59ed739c
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