Summarization
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Safetensors
Italian
t5
text2text-generation
italian
sequence-to-sequence
wikipedia
wits
text-generation-inference
Instructions to use gsarti/it5-large-wiki-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/it5-large-wiki-summarization 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="gsarti/it5-large-wiki-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/it5-large-wiki-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/it5-large-wiki-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f99c320af6aa4ae889a9724b84ba4b0c019044e60e62fb1779520bf7dff9ac4
- Size of remote file:
- 3.13 GB
- SHA256:
- 13c9ab687910bf7638d2d6c843a623e8bf0d4cfb48cb464f1c4608276e5b6156
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