Translation
Transformers
PyTorch
TensorFlow
Safetensors
English
Tigrinya
marian
text2text-generation
Instructions to use Helsinki-NLP/opus-mt-en-ti with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-ti 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-ti")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ti") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-ti", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96df13946a4643d83b045b1b8b4003be7d4d8e9fc4e2e7e09572dc27ffafb153
- Size of remote file:
- 308 MB
- SHA256:
- f32a8a84e8a2bc1b16f6da095dc483b96ef32aa03ed52a498fa3d6f8d7a56078
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