Instructions to use Tugay/clickbait_spoiling_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tugay/clickbait_spoiling_multi with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Tugay/clickbait_spoiling_multi") model = AutoModelForSeq2SeqLM.from_pretrained("Tugay/clickbait_spoiling_multi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from Tugay/clickbait_spoiling_multi: direct link, hf CLI and curl.
- Browser
- Download file 623 Bytes
-
https://huggingface.co/Tugay/clickbait_spoiling_multi/resolve/main/scheduler.pt
- Command line
-
hf download hf://Tugay/clickbait_spoiling_multi/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/Tugay/clickbait_spoiling_multi/resolve/main/scheduler.pt
623 Bytes
- Xet hash:
- 44bf9c3440517b589c1a3aac2aeca7edbf3dd39547f9140930c5115bedca9ff4
- Size of remote file:
- 623 Bytes
- SHA256:
- df710b214de9719ea54d50a2b61151d41e8e2162b15820017c3b79fe9679b33a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.