Instructions to use kejian/downy-conditional with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/downy-conditional with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/downy-conditional") model = AutoModel.from_pretrained("kejian/downy-conditional", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kejian/downy-conditional: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/kejian/downy-conditional/resolve/main/training_args.bin
- Command line
-
hf download hf://kejian/downy-conditional/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kejian/downy-conditional/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- ea6f181914afebebedfa77d5b93679f31b0c494e759287bc9919a024a3e4bf60
- Size of remote file:
- 3.39 kB
- SHA256:
- cd4e75a464748524a87cb85f71324fc5210a485426bfb3e2249dffb401251fa0
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