Instructions to use Helsinki-NLP/opus-mt-en-cpf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-cpf 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-cpf")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-cpf") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-cpf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-en-cpf: direct link, hf CLI and curl.
- Browser
- Download file 297 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-en-cpf/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-en-cpf/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-en-cpf/resolve/main/pytorch_model.bin
297 MB
- Xet hash:
- d73fdceb55e501e62b7ec40555f5c40762ab59195981c0c3b9529a838761ccd9
- Size of remote file:
- 297 MB
- SHA256:
- a5ffe298085185121d38228e16798a2cf72c45168c4eff7cb8e8103af8bcd574
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.