Instructions to use CAMeL-Lab/arat5-coda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAMeL-Lab/arat5-coda with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/arat5-coda") model = AutoModelForSeq2SeqLM.from_pretrained("CAMeL-Lab/arat5-coda", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CAMeL-Lab/arat5-coda: direct link, hf CLI and curl.
- Browser
- Download file 8.4 MB
-
https://huggingface.co/CAMeL-Lab/arat5-coda/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://CAMeL-Lab/arat5-coda@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CAMeL-Lab/arat5-coda/resolve/refs%2Fpr%2F2/tokenizer.json
8.4 MB
File too large to display, you can check the raw version instead.