Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
mt5
text2text-generation
italian
sequence-to-sequence
newspaper
ilgiornale
repubblica
headline-generation
Instructions to use gsarti/mt5-small-headline-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/mt5-small-headline-generation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/mt5-small-headline-generation") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/mt5-small-headline-generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gsarti/mt5-small-headline-generation: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/gsarti/mt5-small-headline-generation/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gsarti/mt5-small-headline-generation/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gsarti/mt5-small-headline-generation/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- d1f94324ad600201641b47422b38692c51c12a80366b726457e327a7a18133de
- Size of remote file:
- 1.2 GB
- SHA256:
- 915268e70fa21dffe2eb9df9604666f182285ed5cdd1acf7b2dbc3f2a628492d
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