Instructions to use WindyTranslate/translate-sv-ha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-ha 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-ha")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-ha") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-ha", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-ha, with attribution and change statement
4fc93b9 verified - Xet hash:
- e5dca81582850512e0c04e08bdaf29f6c56cdb597052fa924e98e459c5b648a3
- Size of remote file:
- 846 kB
- SHA256:
- c56864f53c800dd92440abc241f2455c92b6523ce76480950db67816ea0db97e
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