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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("gsarti/mt5-small-wiki-summarization") model = AutoModelForMultimodalLM.from_pretrained("gsarti/mt5-small-wiki-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8925a08c1e6d9c218577c2a7185012b0c994f847a0204a5d9cb3f774fd545d95
- Size of remote file:
- 1.2 GB
- SHA256:
- f1a9b73b47939dc04f8489df6f256cfac0c26c8495af2d8c64e2cc61161091b9
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