Instructions to use facebook/nllb-200-1.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/nllb-200-1.3B 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/nllb-200-1.3B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-1.3B") model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-1.3B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/nllb-200-1.3B: direct link, hf CLI and curl.
- Browser
- Download file 5.48 GB
-
https://huggingface.co/facebook/nllb-200-1.3B/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/nllb-200-1.3B/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/nllb-200-1.3B/resolve/main/pytorch_model.bin
5.48 GB
- Xet hash:
- 005ee35078d79d33d772e41c0f0185dd1a92ee8828d22696ed0edab69a1390d9
- Size of remote file:
- 5.48 GB
- SHA256:
- 8a134f26de3677e0b7c47d3e98c199fdb4c85a8c6577448d861af4ff24e2ad3f
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