Instructions to use WindyTranslate/translate-swc-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-swc-en 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-swc-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-swc-en") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-swc-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-swc-en, with attribution and change statement
3e742ca verified - Xet hash:
- 9b6cd7f95fb4f73103b716d7fdf58ec5f8520eb13c3af4e533065816bdf53142
- Size of remote file:
- 817 kB
- SHA256:
- 1decc35a17c00a3445ae00b5aef2231246c5ebcfbb9a69f3f5d97f436b15f32b
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