Instructions to use Helsinki-NLP/opus-mt-bg-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-bg-fr 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-bg-fr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-bg-fr") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-bg-fr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-bg-fr: direct link, hf CLI and curl.
- Browser
- Download file 305 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-bg-fr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-bg-fr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-bg-fr/resolve/main/pytorch_model.bin
305 MB
- Xet hash:
- c69227ec7456c2158bcc23539ce4580f9dce5cd0d5a1147bbf3b7cea49d64064
- Size of remote file:
- 305 MB
- SHA256:
- e6dd1d7a1c7629b0322adef8e35c06985c19509eab9dbf4693bb627031b6095e
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