Instructions to use WindyTranslate/translate-sv-pap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-pap 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-pap")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-pap") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-pap", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-pap, with attribution and change statement
971bd63 verified - Xet hash:
- 59ef7c58250c92c36e2119a0a510345c5f06ad444eac727abb033db9dfd7bcb1
- Size of remote file:
- 855 kB
- SHA256:
- 18a2a0e70617cde21756c949229b2512989b52b83f53e9842d8f2ccc6878502a
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