Instructions to use kejian/cond-lovingly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/cond-lovingly with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/cond-lovingly") model = AutoModel.from_pretrained("kejian/cond-lovingly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kejian/cond-lovingly: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/kejian/cond-lovingly/resolve/main/training_args.bin
- Command line
-
hf download hf://kejian/cond-lovingly/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kejian/cond-lovingly/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 7bbb4e82dc7df40d9346cd4ef8c9da58277c0b26f97b1c4107166fe125b5f859
- Size of remote file:
- 3.45 kB
- SHA256:
- 94e84fc7ae4d14b50d40c53ad07ddb4363c3bdb449abac30e55d8580319c1582
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