Instructions to use WindyTranslate/translate-sv-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-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-sv-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-es, with attribution and change statement
3fc9133 verified - Xet hash:
- 7aa51ad9a2304544fe7300669e0fc383199073613267b9a4b7d60dd7fedf2626
- Size of remote file:
- 825 kB
- SHA256:
- e57105e72d12a120f5350efd0849305662b43e0eb996f59c2536c2a6485dd5a4
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