Instructions to use Helsinki-NLP/opus-mt-tr-eo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-tr-eo 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-tr-eo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tr-eo") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tr-eo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-tr-eo: direct link, hf CLI and curl.
- Browser
- Download file 194 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-tr-eo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-tr-eo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-tr-eo/resolve/main/pytorch_model.bin
194 MB
- Xet hash:
- 9849c257738cc0d9bc26c5266fdc306ef76d6f91d0d67dfea53aa8a1b60507da
- Size of remote file:
- 194 MB
- SHA256:
- 55d3d4c43089a2167d4529f7edb25e5d29c53ab0796ea56898a705073e7964c0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.