Instructions to use WindyTranslate/translate-en-urj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-en-urj 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-en-urj")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-en-urj") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-en-urj", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54ecdae94440dd53dd35f9d04dec9bbf04a1f5850321ef5e514533ac1c99dd41
- Size of remote file:
- 793 kB
- SHA256:
- 87c384816f4e80a39793b22e9f4e17ef688ec3570bc3b6b8e56841046a7edb01
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