Instructions to use Helsinki-NLP/opus-mt-lt-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-lt-tr 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="Helsinki-NLP/opus-mt-lt-tr")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-lt-tr") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-lt-tr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dccc7c491af9d9c6b1639c6910ae0a0eb323ec3702fc8227ca06da8cc5ad534b
- Size of remote file:
- 305 MB
- SHA256:
- 10d5defe56e0b011be2abaa925abf03362de17609cd6513b4e5d56e394e9ff68
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