Instructions to use WindyTranslate/translate-swc-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-swc-es 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-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-swc-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-swc-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-swc-es, with attribution and change statement
035180a verified - Xet hash:
- bff1c548e347ece02378863450e7e5fe3982ba126a28458a752a948f431976e4
- Size of remote file:
- 817 kB
- SHA256:
- 50ba191ed4cabe9b07cbeb1f561c1781a01f6382740fe8dcfc21539a614214ff
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