Summarization
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
mt5
text2text-generation
italian
sequence-to-sequence
wikipedia
wits
Instructions to use gsarti/mt5-small-wiki-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/mt5-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/mt5-small-wiki-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/mt5-small-wiki-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/mt5-small-wiki-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47bd2a0f35ae390aad43b0fef2e50ff6b50fd34f5b9001163b68bed57e7ce2bd
- Size of remote file:
- 1.2 GB
- SHA256:
- 4b6bacb5530934f487ce5e2941f31cd8fb2c20ad64544c0402c0351e996c16b1
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