Instructions to use stas/tiny-wmt19-en-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stas/tiny-wmt19-en-de with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("stas/tiny-wmt19-en-de") model = AutoModelForSeq2SeqLM.from_pretrained("stas/tiny-wmt19-en-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from stas/tiny-wmt19-en-de: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://stas/tiny-wmt19-en-de/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/pytorch_model.bin
1.36 MB
- Xet hash:
- c13bd5e2aeda0b5c40e076eac52b0ec15cef855b7bc2a0eccab02987284decc3
- Size of remote file:
- 1.36 MB
- SHA256:
- eb3e5e44a6ae38bf69e95ec714670e421a0ea44e8ffcfb5bf5234459aca38514
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