Instructions to use hawalurahman/idt5-base-mcqg-RACE-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hawalurahman/idt5-base-mcqg-RACE-id with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hawalurahman/idt5-base-mcqg-RACE-id") model = AutoModelForSeq2SeqLM.from_pretrained("hawalurahman/idt5-base-mcqg-RACE-id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from hawalurahman/idt5-base-mcqg-RACE-id: direct link, hf CLI and curl.
- Browser
- Download file 756 kB
-
https://huggingface.co/hawalurahman/idt5-base-mcqg-RACE-id/resolve/main/spiece.model
- Command line
-
hf download hf://hawalurahman/idt5-base-mcqg-RACE-id/spiece.model
-
curl -L -o spiece.model https://huggingface.co/hawalurahman/idt5-base-mcqg-RACE-id/resolve/main/spiece.model
756 kB
- Xet hash:
- 1509a3968d05d36d1a85f8398af6a04476d8d11b290596fd02633d12df62bb46
- Size of remote file:
- 756 kB
- SHA256:
- b39597f7314c28967f391a33e2b6b7656e0fa04348be13015ad044347397385b
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