Instructions to use kejian/debug-pt-conditional with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/debug-pt-conditional with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/debug-pt-conditional") model = AutoModel.from_pretrained("kejian/debug-pt-conditional", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kejian/debug-pt-conditional: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/kejian/debug-pt-conditional/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://kejian/debug-pt-conditional@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kejian/debug-pt-conditional/resolve/refs%2Fpr%2F1/training_args.bin
3.39 kB
- Xet hash:
- 6419da67402ec7f31adcf324d56aa312ee009d15c8710585597e151b604e17e4
- Size of remote file:
- 3.39 kB
- SHA256:
- a4e1de143a346134b48eeb8e53dee538b9629bd2ac1815c9ff4c63785678812b
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