Instructions to use Helsinki-NLP/opus-mt-en-sq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-sq 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-en-sq")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-sq") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-sq", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a12a9c8f04a70e8b4077ea1fabf0d1e8a065e8f487f7292f1072d0052f17bfcd
- Size of remote file:
- 300 MB
- SHA256:
- 337b1f62c063fd20837bbffcbf9aa3f4569f71b41e97ffa9ff34402405cb2d15
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