Instructions to use WindyTranslate/translate-sv-chk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-chk 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-chk")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-chk") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-chk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-chk, with attribution and change statement
78967f0 verified - Xet hash:
- f033287edd008cc4baad22730d2b5bb2f6f9554cef88cb34ffd2aa8edbc9c346
- Size of remote file:
- 848 kB
- SHA256:
- 94dc6444c77e4e284647e499816c483e3fb0cb582208b6930d73b29a0aca14e1
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