Instructions to use dtorber/NAS-bilingue-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/NAS-bilingue-final with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/NAS-bilingue-final") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/NAS-bilingue-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dtorber/NAS-bilingue-final: direct link, hf CLI and curl.
- Browser
- Download file 1.66 GB
-
https://huggingface.co/dtorber/NAS-bilingue-final/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dtorber/NAS-bilingue-final/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dtorber/NAS-bilingue-final/resolve/main/pytorch_model.bin
1.66 GB
- Xet hash:
- 6c375e1836c9cade0612e3f5bec2d6c6f91d26236c42f963ede39bc5a3877ac5
- Size of remote file:
- 1.66 GB
- SHA256:
- a31455ecbf8c898491f4668dc2b32fbe7f917b872651863d86ef4759dfdffeb5
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