Instructions to use HiTZ/mt-hitz-en-eu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/mt-hitz-en-eu with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("HiTZ/mt-hitz-en-eu") model = AutoModelForSeq2SeqLM.from_pretrained("HiTZ/mt-hitz-en-eu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HiTZ/mt-hitz-en-eu: direct link, hf CLI and curl.
- Browser
- Download file 105 MB
-
https://huggingface.co/HiTZ/mt-hitz-en-eu/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HiTZ/mt-hitz-en-eu/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HiTZ/mt-hitz-en-eu/resolve/main/pytorch_model.bin
105 MB
- Xet hash:
- 83d55adc8c6dd21f4c13693b04a487c233ff1d23c67317f1b627c026eb9f0d33
- Size of remote file:
- 105 MB
- SHA256:
- 1d898ab5cd17eb7270275c182e4f299c339c38a4cc355544bccdeede0ad95bef
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.