Instructions to use weitung8/ntuadlhw2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use weitung8/ntuadlhw2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("weitung8/ntuadlhw2") model = AutoModelForSeq2SeqLM.from_pretrained("weitung8/ntuadlhw2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from weitung8/ntuadlhw2: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/weitung8/ntuadlhw2/resolve/main/tokenizer.json
- Command line
-
hf download hf://weitung8/ntuadlhw2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/weitung8/ntuadlhw2/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 7b18d220688638622067ba1911e052f51d0cbdaacd4f1b29d4862f9c48fd6b38
- Size of remote file:
- 16.3 MB
- SHA256:
- 4ebf4569386813d4b10b8198e64a3c0cdd75cd8ad27824426b3a558e7e861053
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.