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 pytorch_model.bin from Tugay/clickbait_spoiling_phrase: direct link, hf CLI and curl.
- Browser
- Download file 2.95 GB
-
https://huggingface.co/Tugay/clickbait_spoiling_phrase/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Tugay/clickbait_spoiling_phrase/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Tugay/clickbait_spoiling_phrase/resolve/main/pytorch_model.bin
2.95 GB
- Xet hash:
- 4cd06c651c8296986a51ea5ceff1cd787ab63b6b5f5bc5bcfada9085cca13918
- Size of remote file:
- 2.95 GB
- SHA256:
- 61b47d27b7f915ad35e5e3b60d23300cc642f6daa2ffb724f4162954156015d5
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