Instructions to use masakhane/afrimbart_fr_mos_news with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use masakhane/afrimbart_fr_mos_news with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("masakhane/afrimbart_fr_mos_news") model = AutoModelForSeq2SeqLM.from_pretrained("masakhane/afrimbart_fr_mos_news", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from masakhane/afrimbart_fr_mos_news: direct link, hf CLI and curl.
- Browser
- Download file 2.44 GB
-
https://huggingface.co/masakhane/afrimbart_fr_mos_news/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://masakhane/afrimbart_fr_mos_news/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/masakhane/afrimbart_fr_mos_news/resolve/main/pytorch_model.bin
2.44 GB
- Xet hash:
- b9bbbda465acbea0d5f8822eac655e4ab2607a059994b949ebff8e674291db79
- Size of remote file:
- 2.44 GB
- SHA256:
- 144ca9d383d7d8fcce42c606af7ed9b8b5b784017d6d3c199b770ce71f821959
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