Instructions to use Pollawat/mt5-small-thai-qg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pollawat/mt5-small-thai-qg with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Pollawat/mt5-small-thai-qg") model = AutoModelForSeq2SeqLM.from_pretrained("Pollawat/mt5-small-thai-qg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Pollawat/mt5-small-thai-qg: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/Pollawat/mt5-small-thai-qg/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Pollawat/mt5-small-thai-qg/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Pollawat/mt5-small-thai-qg/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- 5a268b4936c30717c5033c6badfdaa79234b2cd0dd494529bddd71acb0f2710e
- Size of remote file:
- 1.2 GB
- SHA256:
- 0aabea2c51ecdc14d1eb405b7108de8441a87bafcfac083aa14579c7276bd43b
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