Transformers
Safetensors
Arabic
t5
text2text-generation
AraT5
Arabic
Distractor-Generation
text-generation-inference
Instructions to use Nouran30/distractor-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nouran30/distractor-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Nouran30/distractor-model") model = AutoModelForSeq2SeqLM.from_pretrained("Nouran30/distractor-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Nouran30/distractor-model: direct link, hf CLI and curl.
- Browser
- Download file 15.3 MB
-
https://huggingface.co/Nouran30/distractor-model/resolve/main/tokenizer.json
- Command line
-
hf download hf://Nouran30/distractor-model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Nouran30/distractor-model/resolve/main/tokenizer.json
15.3 MB
- Xet hash:
- 52c67315a9917a782c5a786ce3e7e17b115af318415ee74082a6fd77e60cdd45
- Size of remote file:
- 15.3 MB
- SHA256:
- b0dcab48b44ccabdfb69ea2a8329f4b5cecb899d49f3339abfe520012aa85f7f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.