Instructions to use WindyTranslate/translate-sv-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-st 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-st")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-st") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-st", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-st, with attribution and change statement
49c53da verified - Xet hash:
- f9937182cc192c29fa2e1ca1c8dcd08dcc3ec1755b6176ca3dd5e29cec8c0b45
- Size of remote file:
- 854 kB
- SHA256:
- a2405356d42276dd82c280a35d4a392c747086323a16dc8aabde8f4ed600caca
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