Instructions to use WindyTranslate/translate-sv-mos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-mos 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-mos")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-mos") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-mos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-mos, with attribution and change statement
3a6e2bc verified - Xet hash:
- b2c6806663ed7f6a4f8aa488f0592af79c219b6c68adc40555059414de04221f
- Size of remote file:
- 842 kB
- SHA256:
- 79e382e23afa6c047a24318682033413ca172f72170090490960a0835101ae8d
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