Instructions to use WindyTranslate/translate-sv-ve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-ve 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-ve")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-ve") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-ve", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-ve, with attribution and change statement
9ba6722 verified - Xet hash:
- 37a32e3e8fa1571a64025744888ba2c48aad6c30382ed698dc49cbf0fef8e821
- Size of remote file:
- 848 kB
- SHA256:
- db37df4a0774ce506c0e4faa9494a4a4e8466f36eccf57e3f52fadcf7e705215
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