Instructions to use WindyTranslate/translate-en-afa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-en-afa 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-afa")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-en-afa") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-en-afa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2666fa733248361e83e37cb3b9c57b057dfd364be330bc4e0a554cc634ec0ba6
- Size of remote file:
- 808 kB
- SHA256:
- 3321c5925744f6b35925f48e51c5eee518ca52b5f519f6a1570e9553bad93ddc
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