Instructions to use Narsil/nllb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/nllb 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="Narsil/nllb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Narsil/nllb") model = AutoModelForSeq2SeqLM.from_pretrained("Narsil/nllb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Narsil/nllb: direct link, hf CLI and curl.
- Browser
- Download file 2.46 GB
-
https://huggingface.co/Narsil/nllb/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Narsil/nllb/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Narsil/nllb/resolve/main/pytorch_model.bin
2.46 GB
- Xet hash:
- 44e942c185321f9ee96e51eb31c9cf8c4f613215fa0c5a9035e9b71ede516fba
- Size of remote file:
- 2.46 GB
- SHA256:
- c266c2cfd19758b6d09c1fc31ecdf1e485509035f6b51dfe84f1ada83eefcc42
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