Instructions to use rooftopcoder/tst-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rooftopcoder/tst-summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rooftopcoder/tst-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("rooftopcoder/tst-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from rooftopcoder/tst-summarization: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/rooftopcoder/tst-summarization/resolve/caca0cdffd0f93feb68845e255164469c0935f35/tokenizer.json
- Command line
-
hf download hf://rooftopcoder/tst-summarization@caca0cdffd0f93feb68845e255164469c0935f35/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/rooftopcoder/tst-summarization/resolve/caca0cdffd0f93feb68845e255164469c0935f35/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.