Instructions to use ARTeLab/it5-summarization-fanpage-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ARTeLab/it5-summarization-fanpage-64 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="ARTeLab/it5-summarization-fanpage-64")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ARTeLab/it5-summarization-fanpage-64") model = AutoModelForSeq2SeqLM.from_pretrained("ARTeLab/it5-summarization-fanpage-64") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44e12b04495e1445e104b2b5ab0f38ac406966d97f6b1d9b27fb91010e31a34a
- Size of remote file:
- 990 MB
- SHA256:
- e095685c7e6b6aa22c62ae31faebbdbb176b1e08e7dbc144281ccfb2feb9cd69
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.