Instructions to use madatnlp/mbart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madatnlp/mbart with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("madatnlp/mbart") model = AutoModelForSeq2SeqLM.from_pretrained("madatnlp/mbart", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from madatnlp/mbart: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/madatnlp/mbart/resolve/main/tokenizer.json
- Command line
-
hf download hf://madatnlp/mbart/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/madatnlp/mbart/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 57dab974846c5200a938cad1b8862611b783350d8170d041a4f6c0bb3915f6cf
- Size of remote file:
- 17.1 MB
- SHA256:
- b6f79e63b44bbdfdd3dd0a27b579484e48b2ed12239310ff3efb5de6e635c471
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.