Summarization
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
t5
text2text-generation
italian
sequence-to-sequence
wikipedia
wits
text-generation-inference
Instructions to use gsarti/it5-base-wiki-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/it5-base-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-base-wiki-summarization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/it5-base-wiki-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/it5-base-wiki-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from gsarti/it5-base-wiki-summarization: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/gsarti/it5-base-wiki-summarization/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://gsarti/it5-base-wiki-summarization/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/gsarti/it5-base-wiki-summarization/resolve/main/flax_model.msgpack
990 MB
- Xet hash:
- d485d53a38123a8ec8ef800ace292f56e774af08ce5388d026fa30814666fa2c
- Size of remote file:
- 990 MB
- SHA256:
- 13b1973892d2c6a9c0dc2eeb64bc28b5fdf85874db5f74d35e38c251d79a21a7
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