Instructions to use kejian/cond-lovingly-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/cond-lovingly-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/cond-lovingly-base") model = AutoModel.from_pretrained("kejian/cond-lovingly-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kejian/cond-lovingly-base: direct link, hf CLI and curl.
- Browser
- Download file 457 MB
-
https://huggingface.co/kejian/cond-lovingly-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kejian/cond-lovingly-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kejian/cond-lovingly-base/resolve/main/pytorch_model.bin
457 MB
- Xet hash:
- 74b7a14dd128e5007012f42abf7142689fbfffce5b834d5cbbd47ac526b6bc0a
- Size of remote file:
- 457 MB
- SHA256:
- 4f6d0895703119ea03426038d9c90ab7dcfde246f69e1c3e3f6267c77b3e63e7
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