Instructions to use WindyTranslate/translate-en-gem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-en-gem 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-gem")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-en-gem") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-en-gem", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 575748e7af25a8886697a0e008c6b35e49d7cf705e6c2a336c77d468aec5f49a
- Size of remote file:
- 784 kB
- SHA256:
- 415b3b869faf3d9037c9700a5edc358ebe6406971043d1d89f8a13f3d1d70b27
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