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 optimizer.pt from Tugay/clickbait_spoiling_phrase: direct link, hf CLI and curl.
- Browser
- Download file 5.9 GB
-
https://huggingface.co/Tugay/clickbait_spoiling_phrase/resolve/main/optimizer.pt
- Command line
-
hf download hf://Tugay/clickbait_spoiling_phrase/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Tugay/clickbait_spoiling_phrase/resolve/main/optimizer.pt
5.9 GB
- Xet hash:
- f6acb3bbef8754a4bda0a57d1faded4e904667bae4b6faa3e241aeedf164c8c6
- Size of remote file:
- 5.9 GB
- SHA256:
- 0ad6b9b09afcedfe277d5f59da0b9e42cce9db2c823dbb1419796e6d87b60913
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.