Instructions to use intanm/clickbait_spoiling_model_trial_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intanm/clickbait_spoiling_model_trial_2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="intanm/clickbait_spoiling_model_trial_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("intanm/clickbait_spoiling_model_trial_2") model = AutoModelForQuestionAnswering.from_pretrained("intanm/clickbait_spoiling_model_trial_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from intanm/clickbait_spoiling_model_trial_2: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/intanm/clickbait_spoiling_model_trial_2/resolve/main/training_args.bin
- Command line
-
hf download hf://intanm/clickbait_spoiling_model_trial_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/intanm/clickbait_spoiling_model_trial_2/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 43160b9e28ab9637378970a619d29f8f0dd1837f933ba48d665f2adfa7d1780f
- Size of remote file:
- 3.52 kB
- SHA256:
- 7f5f14fb4e4f636c3f1d89b22295834b891105c4177bca1b47e8684761fd3920
路
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