Instructions to use rjarun20/dnu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rjarun20/dnu with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rjarun20/dnu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from rjarun20/dnu: direct link, hf CLI and curl.
- Browser
- Download file 115 Bytes
-
https://huggingface.co/rjarun20/dnu/resolve/main/generation_config.json
- Command line
-
hf download hf://rjarun20/dnu/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/rjarun20/dnu/resolve/main/generation_config.json
115 Bytes
- Xet hash:
- ca399a8241c2f96193e236a7f7bf943930501854e345b4fc493797f358e1eee7
- Size of remote file:
- 115 Bytes
- SHA256:
- 29aab0082245b7441e538624af62c0ab106a13ac7450cf6a6545a8a4ea5679d4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.