Instructions to use SXUCFN/CFNParser-AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SXUCFN/CFNParser-AI with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SXUCFN/CFNParser-AI") model = AutoModel.from_pretrained("SXUCFN/CFNParser-AI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SXUCFN/CFNParser-AI: direct link, hf CLI and curl.
- Browser
- Download file 410 MB
-
https://huggingface.co/SXUCFN/CFNParser-AI/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://SXUCFN/CFNParser-AI@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SXUCFN/CFNParser-AI/resolve/refs%2Fpr%2F1/pytorch_model.bin
410 MB
- Xet hash:
- 2cc49cdb46d3f4a1c48678b81b7f45a37173a2ab95d5f5bf1fcfaf7923e82602
- Size of remote file:
- 410 MB
- SHA256:
- a918896f1afba9ede6d80df4360f3dd7c5cadd794aa84be371b0568b37fcfa19
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