Instructions to use WindyTranslate/translate-sv-cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-cs 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-cs")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-cs") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote herm0 build from WindstormLabs/translate-sv-cs, with attribution and change statement
1c609b1 verified - Xet hash:
- fd1f67d4c75520797cb026e35f5c129c21e9112e25389be6e62caba6f7dfd830
- Size of remote file:
- 815 kB
- SHA256:
- 45d677c69334b29c27b8649473e1adbbe2029cd4cd9533e6f2f26e2d286f2dfb
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