Instructions to use biunlp/LongMt5-HeSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biunlp/LongMt5-HeSum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("biunlp/LongMt5-HeSum") model = AutoModelForSeq2SeqLM.from_pretrained("biunlp/LongMt5-HeSum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from biunlp/LongMt5-HeSum: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/biunlp/LongMt5-HeSum/resolve/main/tokenizer.json
- Command line
-
hf download hf://biunlp/LongMt5-HeSum/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/biunlp/LongMt5-HeSum/resolve/main/tokenizer.json
16.8 MB
- Xet hash:
- 2e982988b65973af16e70f458959328dc28259fb7351e94fab663ac851b6591f
- Size of remote file:
- 16.8 MB
- SHA256:
- a416fd933a63d0a076ce7f825f791fa20e11de78cf1be138765bf58d186eb910
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.