Instructions to use JayRay5/DIVE-Doc-ARD-HRes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JayRay5/DIVE-Doc-ARD-HRes with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import DIVEdoc model = DIVEdoc.from_pretrained("JayRay5/DIVE-Doc-ARD-HRes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from JayRay5/DIVE-Doc-ARD-HRes: direct link, hf CLI and curl.
- Browser
- Download file 4.26 MB
-
https://huggingface.co/JayRay5/DIVE-Doc-ARD-HRes/resolve/main/tokenizer.model
- Command line
-
hf download hf://JayRay5/DIVE-Doc-ARD-HRes/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/JayRay5/DIVE-Doc-ARD-HRes/resolve/main/tokenizer.model
4.26 MB
- Xet hash:
- f783b931a0a2d5b2a14174712a7f55393c0ca4fb62c8ade07dd9b5f07c3051bb
- Size of remote file:
- 4.26 MB
- SHA256:
- 8986bb4f423f07f8c7f70d0dbe3526fb2316056c17bae71b1ea975e77a168fc6
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