Summarization
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
t5
text2text-generation
italian
sequence-to-sequence
wikipedia
wits
text-generation-inference
Instructions to use gsarti/it5-small-wiki-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/it5-small-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-small-wiki-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/it5-small-wiki-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/it5-small-wiki-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a19a97b9344b28640d4e0d2099ab9c9a9ea55b9f0f7deaa4971efe84df0c531
- Size of remote file:
- 308 MB
- SHA256:
- 411731951a3c07ad1f5af8f0603a3c048d6a3f4aa3d030e95ee56d304ff6fe6c
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