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 tokenizer_config.json from rjarun20/dnu: direct link, hf CLI and curl.
- Browser
- Download file 1.6 kB
-
https://huggingface.co/rjarun20/dnu/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://rjarun20/dnu/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/rjarun20/dnu/resolve/main/tokenizer_config.json
1.6 kB
- Xet hash:
- 07f26d436a2d62b80e40bf83621679aa1ed5f8f448b418bfa6c030d1a33f04e4
- Size of remote file:
- 1.6 kB
- SHA256:
- d18047adbaef0ed9719dcd0927f50460c6523236156397988a64f73be619e1cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.