Instructions to use ajayarora1235/outputs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajayarora1235/outputs with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ajayarora1235/outputs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ajayarora1235/outputs: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/ajayarora1235/outputs/resolve/main/tokenizer.json
- Command line
-
hf download hf://ajayarora1235/outputs/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ajayarora1235/outputs/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 363e4cdd84a26308e880b2edb7d1c32e8118b6e642315a1f4ac625d43c6e5d8c
- Size of remote file:
- 17.1 MB
- SHA256:
- 3f0a9c36fb297452029a786652fd2a7ad7eea9fd6ff802ad083f7f747a4a3875
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.