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 tokenizer.json from Narsil/nllb: direct link, hf CLI and curl.
- Browser
- Download file 17.3 MB
-
https://huggingface.co/Narsil/nllb/resolve/main/tokenizer.json
- Command line
-
hf download hf://Narsil/nllb/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Narsil/nllb/resolve/main/tokenizer.json
17.3 MB
- Xet hash:
- 0202f54e596c03be98c5a537e9214967476071dce868ac20a7a42ad57fdd1f7b
- Size of remote file:
- 17.3 MB
- SHA256:
- e316b82de11d0f951f370943b3c438311629547285129b0b81dadabd01bca665
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