Instructions to use Tugay/clickbait_spoiling_phrase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tugay/clickbait_spoiling_phrase with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Tugay/clickbait_spoiling_phrase") model = AutoModelForSeq2SeqLM.from_pretrained("Tugay/clickbait_spoiling_phrase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Tugay/clickbait_spoiling_phrase: direct link, hf CLI and curl.
- Browser
- Download file 3.57 kB
-
https://huggingface.co/Tugay/clickbait_spoiling_phrase/resolve/main/training_args.bin
- Command line
-
hf download hf://Tugay/clickbait_spoiling_phrase/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Tugay/clickbait_spoiling_phrase/resolve/main/training_args.bin
3.57 kB
- Xet hash:
- 77d2cd479324a0ed39f96cb1b1969872a41dbb5ab51fedbb58e9280c447911b3
- Size of remote file:
- 3.57 kB
- SHA256:
- 96b74ceb860c6465cabaae3a08f61bab6b323962121fce771d402e6ac5d8b30a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.