Instructions to use Helsinki-NLP/opus-mt-th-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-th-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-th-fr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-th-fr") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-th-fr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-th-fr: direct link, hf CLI and curl.
- Browser
- Download file 306 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-th-fr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-th-fr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-th-fr/resolve/main/pytorch_model.bin
306 MB
- Xet hash:
- 37006568d3054412c8a7b4294187552c2223e6ac70133626578a75e7d4126b65
- Size of remote file:
- 306 MB
- SHA256:
- f3bcef55a39bee30a3a259c40fe98f3ef916f51caaeb65a0d7f449a6321e122b
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