Instructions to use WindyTranslate/translate-en-tut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-en-tut 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-tut")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-en-tut") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-en-tut", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85f297da95e464bd9c315931bcbcee54f984b47dfe93213b679e817f9b67b51d
- Size of remote file:
- 804 kB
- SHA256:
- b1bf56f8f864d841ffc944df79d687ba8b0b8d88499e6987bd4b6df70c3bcfad
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