Instructions to use WindyTranslate/translate-pis-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-pis-sv 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-pis-sv")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-pis-sv") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-pis-sv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-pis-sv, with attribution and change statement
c5831c9 verified - Xet hash:
- cf2fd3fea37911bc92dc3c23df3ac401a8d7efdb3dd48c5c41a81031d159fd59
- Size of remote file:
- 587 kB
- SHA256:
- 7f1774dfe690ed77cd558ac3c159c2798656037d4caa38ef014a17324f8db766
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