Instructions to use facebook/mbart-large-cc25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mbart-large-cc25 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="facebook/mbart-large-cc25")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("facebook/mbart-large-cc25") model = AutoModelForSeq2SeqLM.from_pretrained("facebook/mbart-large-cc25", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/mbart-large-cc25: direct link, hf CLI and curl.
- Browser
- Download file 2.44 GB
-
https://huggingface.co/facebook/mbart-large-cc25/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/mbart-large-cc25/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/mbart-large-cc25/resolve/main/pytorch_model.bin
2.44 GB
- Xet hash:
- 2cd9aa72e7be464d723acb54ff3797b5ec6920123b6c847f64302c012495d994
- Size of remote file:
- 2.44 GB
- SHA256:
- 6e55bd7b105d99e6e25fafd4125cd5acb956ad2daef209b74fc4fb72113dcf84
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