Instructions to use WindyTranslate/translate-de-pag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-de-pag with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="WindyTranslate/translate-de-pag")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-de-pag") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-de-pag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cab8b53c174737657da00a8eb949ff207cd1c1de5c041a6c222b30998396a15a
- Size of remote file:
- 864 kB
- SHA256:
- b1b0d17873fb8e0246a386ac66341244a34fd2189251cdde38fc91a5610d7fc5
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