Instructions to use kaejo98/bart-base_question_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaejo98/bart-base_question_generation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kaejo98/bart-base_question_generation") model = AutoModelForSeq2SeqLM.from_pretrained("kaejo98/bart-base_question_generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kaejo98/bart-base_question_generation: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/kaejo98/bart-base_question_generation/resolve/main/training_args.bin
- Command line
-
hf download hf://kaejo98/bart-base_question_generation/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kaejo98/bart-base_question_generation/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 618220106f2d4fe9aae0abae568e89f7700ebd04b238087276f47c345b939999
- Size of remote file:
- 3.45 kB
- SHA256:
- b52dbb6b0667421387c800a1ddef2b9b1e287cdb0d6f6fe0a4d15f0d0e9a3f9b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.