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:
- 0028624e040a3a6de64f1472c157df38ad04ae6d105d8e74d74271efd6410e80
- Size of remote file:
- 707 kB
- SHA256:
- c4a99ea3602b29fbf901ade8b93a45efa3d7c64eab8fc5fa812383efa327a87d
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