Instructions to use WindyTranslate/translate-es-et with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-es-et 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-es-et")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-es-et") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-es-et", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea8bbd07d036ebb22ec5a011c5cddc940d39447c1a13b25d0b77c7d932b8b982
- Size of remote file:
- 815 kB
- SHA256:
- 707a2456a42189c0659399e6490c402b90ed4665f6fab23ff8c25494b2f7b2ca
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