Instructions to use WindyTranslate/translate-sv-ase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-ase 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-ase")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-ase") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-ase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-ase, with attribution and change statement
84c1205 verified - Xet hash:
- 95e33695e8c049c002587c89475a3ba88a78bbbccff8891e03b75145baea0fcd
- Size of remote file:
- 781 kB
- SHA256:
- f4268238dcdf390a2ea7b3e3f934555978695e69d6890d63b92af271ed1fa7f5
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