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 checkpoint-5000/optimizer.pt from kejian/cond-lovingly: direct link, hf CLI and curl.
- Browser
- Download file 888 MB
-
https://huggingface.co/kejian/cond-lovingly/resolve/main/checkpoint-5000/optimizer.pt
- Command line
-
hf download hf://kejian/cond-lovingly/checkpoint-5000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/kejian/cond-lovingly/resolve/main/checkpoint-5000/optimizer.pt
888 MB
- Xet hash:
- 13e8a581a8475e2a0685d7ac1002349855bfa7dae80bffb611d9420a1ac6d45b
- Size of remote file:
- 888 MB
- SHA256:
- b5a396d3f80b40ba3973b146b70130cdc69f5fa00b782f02e3ab30b345daee07
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