Instructions to use FirstPotatoCoder/BacII-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FirstPotatoCoder/BacII-LoRA with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FirstPotatoCoder/BacII-LoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from FirstPotatoCoder/BacII-LoRA: direct link, hf CLI and curl.
- Browser
- Download file 245 MB
-
https://huggingface.co/FirstPotatoCoder/BacII-LoRA/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://FirstPotatoCoder/BacII-LoRA/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/FirstPotatoCoder/BacII-LoRA/resolve/main/adapter_model.safetensors
245 MB
- Xet hash:
- 3b3903c8eb4c5afc0494ff7be34e867a77f38b1342cc7b4f541dc3edd754cdb2
- Size of remote file:
- 245 MB
- SHA256:
- e0c55fec27fd857bea8a905ae598b7f7205ccbea499317cb976a9319288602a4
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