Instructions to use WindyTranslate/translate-st-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-st-es 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-st-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-st-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-st-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-st-es, with attribution and change statement
430b575 verified - Xet hash:
- 672b1d6904f2ca3e1d259b1e2f2c343ae2a946e9e476259234831d02d2758c96
- Size of remote file:
- 823 kB
- SHA256:
- 6a555e5fe071667751423bd4f22c6b0e9009962eab15203f446a6b60b8f927e7
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