Instructions to use WindyTranslate/translate-sv-el with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-el 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-sv-el")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-el") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-el", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-el, with attribution and change statement
7aee827 verified - Xet hash:
- 89d149e0c116d8f21a4a0970718f90f024775e1234cc570071577846884bf5ac
- Size of remote file:
- 821 kB
- SHA256:
- bd541187bd57c91285cfe9404052258d7d42667c95e859ef50f8f3c80d4392a7
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