Summarization
Transformers
PyTorch
Safetensors
Italian
t5
text2text-generation
text-generation-inference
Instructions to use ARTeLab/it5-summarization-fanpage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ARTeLab/it5-summarization-fanpage 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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ARTeLab/it5-summarization-fanpage") model = AutoModelForSeq2SeqLM.from_pretrained("ARTeLab/it5-summarization-fanpage") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d567a7d7581d5370e353de83a64cee91dfc2c399394e06dd68eb4b8b7298b0e8
- Size of remote file:
- 990 MB
- SHA256:
- 1c0524edc93a24fa7f771f42e288519e09498fb9379d71013cd91400f557efe0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.