Translation
Transformers
TensorBoard
Safetensors
PyTorch
Ganda
English
marian
text2text-generation
mlflow
Eval Results (legacy)
Instructions to use openchs/lg-opus-mt-multi-en-synthetic-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openchs/lg-opus-mt-multi-en-synthetic-v1 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="openchs/lg-opus-mt-multi-en-synthetic-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("openchs/lg-opus-mt-multi-en-synthetic-v1") model = AutoModelForSeq2SeqLM.from_pretrained("openchs/lg-opus-mt-multi-en-synthetic-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0b75b23c342699051b43c13c95d4d32dee95ff73f45a09603b6b75f29375543
- Size of remote file:
- 308 MB
- SHA256:
- c8f2318acff89e6a4461b4e94ee1b073446b185769f7a42725ff64b79d4f5e11
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