Instructions to use mbazaNLP/NLLB-Education with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbazaNLP/NLLB-Education with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mbazaNLP/NLLB-Education") model = AutoModelForSeq2SeqLM.from_pretrained("mbazaNLP/NLLB-Education", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mbazaNLP/NLLB-Education: direct link, hf CLI and curl.
- Browser
- Download file 5.48 GB
-
https://huggingface.co/mbazaNLP/NLLB-Education/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mbazaNLP/NLLB-Education/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mbazaNLP/NLLB-Education/resolve/main/pytorch_model.bin
5.48 GB
- Xet hash:
- 26f825708bc79b7fd701f72736968207df40f33ee878595aee866aed2ed73c32
- Size of remote file:
- 5.48 GB
- SHA256:
- 2a2677370d8c4684bdf90f5bf5a10101e0613c43c8deba08989b740ea878e400
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