Instructions to use kejian/cond-lovingly-base-drop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/cond-lovingly-base-drop with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/cond-lovingly-base-drop") model = AutoModel.from_pretrained("kejian/cond-lovingly-base-drop", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kejian/cond-lovingly-base-drop: direct link, hf CLI and curl.
- Browser
- Download file 457 MB
-
https://huggingface.co/kejian/cond-lovingly-base-drop/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kejian/cond-lovingly-base-drop/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kejian/cond-lovingly-base-drop/resolve/main/pytorch_model.bin
457 MB
- Xet hash:
- b43d10fa9155c433694dd7227e035ca62d91eb31155330b9b5c2a3c6ea52b56e
- Size of remote file:
- 457 MB
- SHA256:
- 4da996379d47df4e7c19674271d5eee5da5e8eb3f55b98cd5196cb286cce5689
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