Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
t5
text2text-generation
seq2seq
lm-head
text-generation-inference
Instructions to use gsarti/it5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/it5-small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/it5-small") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/it5-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download opt_state.msgpack from gsarti/it5-small: direct link, hf CLI and curl.
- Browser
- Download file 1.02 MB
-
https://huggingface.co/gsarti/it5-small/resolve/main/opt_state.msgpack
- Command line
-
hf download hf://gsarti/it5-small/opt_state.msgpack
-
curl -L -o opt_state.msgpack https://huggingface.co/gsarti/it5-small/resolve/main/opt_state.msgpack
1.02 MB
- Xet hash:
- e30566f69bde326b5ac45a9cd4dcc63c5f683eaccc8766cf953fed82905216be
- Size of remote file:
- 1.02 MB
- SHA256:
- e7480c903650ed79abbed5c152b703e1e01dc30aa21ad1d6f976f742aa08ccc9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.